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Mistral: Ministral 3 8B 2512
mistralai/ministral-8b-2512 · mistralai · context 262 144 · in $0.150/1M · out $0.150/1M
Global Index
506
95% CI [469–543] · index v0.2.0
Per-domain scores
| Domain | Score (95% CI) | Accuracy (IRT) | Consistency | Calibration | Contam. Δ | p50 | $/1k | |
|---|---|---|---|---|---|---|---|---|
| agentic | 372 [306–437] | 0.171 | 0.73 | 0.23 | 0.019 | 303ms | $0.270 | |
| code | 393 [320–466] | 0.229 | 0.80 | 0.43 | 0.077 | 352ms | $0.120 | |
| instruction following | 299 [230–368] | 0.210 | 0.85 | 0.45 | 0.365 | 323ms | $0.025 | |
| knowledge | 585 [437–732] | 0.469 | 1.00 | 0.90 | 0.115 | 304ms | $0.014 | |
| math | 661 [526–797] | 0.492 | 0.88 | 0.83 | 0.000 | 304ms | $0.064 | |
| multilingual | 456 [393–520] | 0.184 | 0.95 | 0.53 | 0.000 | 291ms | $0.025 | |
| reasoning | 663 [520–806] | 0.607 | 0.97 | 0.90 | 0.115 | 290ms | $0.049 | |
| terminal | 419 [350–489] | 0.193 | 0.84 | 0.27 | 0.000 | 307ms | $0.047 | |
| vision ocr | 705 [541–869] | 0.562 | 1.00 | 0.97 | 0.038 | 670ms | $0.140 |
Every answer, every test
Full transparency: the model's latest graded answer on every instantiated item of the current index version. Answer keys never leave the server; anchor-item prompts are withheld to protect the longitudinal subset.
agentic 7/30 correct
wrongagentic.tools.context-load-v1conf 100% · 1.0s · $0.002 · 5143 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (284 records, format: id|customer|region|item|qty|status):
```
1560|birch|east|sensor|87|paid
2174|harbor|east|cable|50|held
1383|dorian|west|frame|47|pending
2119|cobalt|north|panel|95|held
1498|cobalt|west|rotor|18|paid
1525|gale|east|valve|94|pending
1682|dorian|south|pump|88|pending
1934|ember|east|rotor|89|held
1600|ionic|west|pump|65|paid
2148|cobalt|north|cable|97|held
1479|gale|south|panel|37|shipped
1880|cobalt|south|cable|55|held
1799|juno|south|cable|90|held
1492|gale|west|cable|94|shipped
1602|birch|west|gasket|21|held
2225|gale|east|valve|75|paid
2345|dorian|south|cable|75|pending
2377|harbor|north|valve|95|pending
1688|juno|west|frame|90|held
1621|gale|north|gasket|16|held
2317|juno|north|frame|97|paid
2007|dorian|south|pump|71|paid
2090|juno|north|sensor|11|paid
1569|gale|south|sensor|63|paid
1472|ionic|east|rotor|56|held
1711|gale|south|pump|33|held
1562|acme|north|sensor|88|held
2053|gale|east|cable|24|paid
2134|harbor|east|rotor|73|paid
1872|birch|west|frame|18|paid
2147|ember|north|sensor|69|held
1452|cobalt|north|panel|77|shipped
1912|ember|south|cable|32|pending
1306|acme|east|rotor|43|shipped
1298|acme|east|valve|78|held
2021|gale|north|valve|21|shipped
1277|acme|east|valve|66|held
1354|birch|east|sensor|97|shipped
2144|birch|north|rotor|50|shipped
1969|cobalt|east|panel|95|pending
2115|acme|east|sensor|79|held
2031|ionic|east|cable|15|shipped
1312|acme|south|frame|56|paid
1772|dorian|south|frame|72|pending
1338|fulton|east|rotor|86|held
1783|ember|south|sensor|36|paid
1451|gale|east|cable|22|shipped
1550|cobalt|west|sensor|74|shipped
1726|gale|north|panel|42|shipped
1677|ember|west|pump|16|pending
1328|fulton|south|valve|63|shipped
2236|fulton|east|frame|76|paid
1731|cobalt|north|cable|12|shipped
2402|cobalt|west|frame|36|held
2059|ionic|west|rotor|40|paid
2233|birch|east|rotor|96|paid
1699|ionic|south|rotor|19|shipped
2108|birch|south|gasket|67|paid
2023|ionic|south|panel|60|paid
2153|fulton|west|pump|37|held
1520|gale|south|valve|32|held
1883|birch|west|frame|28|shipped
1992|acme|west|valve|23|held
1327|dorian|south|gasket|80|shipped
1466|gale|west|rotor|83|paid
1395|harbor|south|cable|77|shipped
2217|gale|west|panel|92|paid
1559|ember|south|pump|23|paid
1347|juno|west|pump|63|pending
2187|juno|west|valve|33|shipped
2356|ember|east|valve|85|shipped
1860|ionic|north|frame|69|paid
1976|acme|west|panel|72|pending
1749|ember|east|cable|11|paid
1583|juno|east|cable|60|shipped
2256|harbor|west|frame|22|pending
1702|birch|east|cable|16|pending
1405|fulton|west|frame|31|shipped
1691|harbor|east|gasket|20|shipped
2161|cobalt|east|rotor|17|shipped
2388|acme|north|valve|33|held
1866|ember|south|gasket|76|shipped
1372|cobalt|south|rotor|19|pending
2057|fulton|north|frame|42|paid
1628|juno|north|gasket|14|shipped
1750|juno|south|valve|28|paid
1439|ionic|south|gasket|47|shipped
1754|ember|north|valve|35|paid
1474|gale|east|pump|64|pending
1844|birch|west|frame|74|held
2102|birch|north|gasket|44|pending
1404|birch|east|pump|53|held
1456|birch|west|pump|63|pending
1982|fulton|west|pump|79|held
1261|acme|south|gasket|67|pending
1485|ionic|east|pump|44|pending
2030|dorian|south|gasket|12|paid
2192|gale|east|rotor|27|shipped
1301|acme|east|panel|17|pending
1292|acme|east|rotor|32|pending
2126|dorian|west|cable|34|pending
1436|harbor|east|gasket|61|paid
2210|dorian|west|frame|80|shipped
2017|acme|south|pump|30|pending
1777|dorian|west|rotor|81|paid
2015|dorian|north|frame|68|held
2350|birch|west|frame|77|held
1780|gale|west|cable|81|held
2208|cobalt|west|pump|71|shipped
1608|dorian|east|cable|24|shipped
2290|acme|north|panel|45|pending
1816|acme|north|pump|68|paid
1669|juno|north|gasket|81|pending
1906|gale|east|rotor|33|shipped
1388|harbor|west|panel|30|held
2268|fulton|west|gasket|55|shipped
1886|ember|south|gasket|58|pending
2184|gale|west|gasket|86|held
1490|ember|north|valve|68|pending
1793|birch|west|cable|72|held
2139|ionic|west|valve|62|paid
1258|acme|east|pump|14|pending
1716|gale|south|sensor|11|paid
2169|ember|north|rotor|15|held
1819|acme|north|valve|56|paid
1829|dorian|east|sensor|77|paid
2368|ionic|east|valve|14|shipped
2339|ember|east|panel|24|pending
1932|harbor|north|valve|43|pending
1721|harbor|north|rotor|37|held
2048|juno|west|panel|63|held
1280|acme|east|cable|53|pending
1503|acme|east|panel|85|shipped
1399|ionic|west|valve|20|held
1705|gale|east|frame|43|shipped
1494|fulton|west|rotor|54|held
1414|birch|west|pump|54|paid
1591|ionic|east|valve|91|held
2251|birch|east|panel|39|pending
1425|dorian|south|pump|96|pending
2261|juno|north|sensor|71|paid
2051|gale|east|rotor|31|shipped
1850|cobalt|north|rotor|39|shipped
1885|acme|east|panel|95|held
2269|dorian|west|cable|52|shipped
1419|juno|east|sensor|94|held
1841|ionic|north|rotor|27|pending
2395|fulton|south|valve|77|held
1379|harbor|south|pump|63|shipped
1649|cobalt|east|sensor|61|paid
1810|birch|east|frame|21|shipped
1971|dorian|east|pump|38|paid
1530|dorian|south|pump|70|held
2066|juno|east|rotor|81|pending
1987|cobalt|north|cable|90|pending
1597|juno|south|sensor|22|held
1271|acme|east|frame|50|pending
2363|juno|east|rotor|40|paid
2104|gale|east|gasket|29|held
1742|harbor|south|panel|59|pending
2243|cobalt|south|sensor|90|paid
2197|harbor|south|gasket|61|paid
2114|gale|west|pump|17|pending
2372|gale|east|panel|86|pending
2248|juno|south|sensor|34|shipped
1431|cobalt|north|pump|50|pending
1761|cobalt|north|rotor|22|paid
2013|cobalt|south|cable|61|paid
1371|gale|north|pump|66|held
1281|acme|west|cable|95|pending
1692|fulton|west|frame|20|shipped
1612|ember|north|sensor|24|pending
2045|cobalt|east|gasket|23|held
1643|dorian|north|valve|93|pending
1878|acme|east|pump|57|held
1672|birch|north|sensor|28|paid
2382|fulton|north|gasket|30|paid
1275|acme|north|rotor|43|pending
2327|acme|west|pump|77|held
1748|cobalt|west|gasket|63|paid
2001|ionic|west|frame|52|shipped
1446|fulton|west|valve|61|paid
2229|harbor|south|frame|67|shipped
2188|juno|north|frame|55|paid
1265|acme|east|gasket|63|paid
1366|gale|west|gasket|82|shipped
2203|ionic|south|panel|99|pending
1638|juno|east|pump|70|paid
2181|acme|west|rotor|12|pending
1779|juno|north|valve|74|held
1409|harbor|north|pump|87|held
1296|acme|north|cable|24|pending
1553|fulton|west|sensor|46|shipped
2036|ionic|west|gasket|37|pending
1957|harbor|south|gasket|26|held
1547|gale|east|rotor|79|pending
1786|harbor|east|sensor|95|shipped
2249|cobalt|south|cable|63|paid
1477|gale|west|pump|54|shipped
1875|acme|west|frame|98|paid
1448|ionic|east|panel|70|held
1340|harbor|north|sensor|89|pending
1305|acme|west|cable|84|pending
2086|dorian|east|cable|98|pending
1631|acme|south|frame|88|shipped
2305|gale|east|sensor|54|shipped
2150|ember|east|pump|53|pending
1308|fulton|south|frame|97|shipped
1668|acme|north|frame|49|held
2242|harbor|west|pump|57|held
1545|cobalt|west|rotor|34|paid
1532|fulton|east|valve|23|paid
1859|fulton|east|valve|63|paid
1654|fulton|west|frame|37|pending
1335|ionic|north|gasket|56|paid
1635|dorian|north|rotor|10|held
1329|gale|east|sensor|15|shipped
2252|birch|north|frame|97|shipped
1899|harbor|west|sensor|33|paid
2154|gale|north|panel|77|pending
1360|harbor|west|pump|82|paid
1687|gale|west|frame|46|held
2297|fulton|west|gasket|28|pending
1613|fulton|west|sensor|99|held
1939|dorian|north|frame|78|shipped
2128|acme|east|frame|62|held
1558|harbor|south|valve|19|held
2263|ionic|south|sensor|31|shipped
1286|acme|east|rotor|80|shipped
1516|gale|south|gasket|65|paid
2381|fulton|south|frame|91|pending
1576|juno|west|frame|44|pending
1670|fulton|north|frame|22|pending
1857|ember|north|cable|89|shipped
1666|fulton|north|gasket|16|shipped
1440|ionic|north|sensor|18|held
2096|juno|east|frame|37|held
1737|acme|south|rotor|38|shipped
1892|cobalt|west|pump|59|paid
2333|fulton|west|panel|69|held
2041|harbor|south|frame|58|paid
1798|acme|east|frame|47|paid
2312|acme|north|sensor|70|shipped
1952|juno|east|cable|70|held
2080|juno|east|pump|17|paid
1838|harbor|west|cable|74|held
1538|fulton|east|rotor|50|paid
1824|acme|east|pump|32|shipped
2320|ember|west|frame|87|shipped
2220|fulton|west|sensor|88|held
1730|harbor|south|frame|12|shipped
2279|juno|west|panel|29|shipped
1509|acme|west|gasket|67|shipped
1974|acme|west|rotor|54|held
1318|birch|south|panel|43|shipped
2163|cobalt|west|panel|22|pending
2304|fulton|north|frame|42|shipped
1648|juno|north|gasket|76|paid
2283|ionic|north|valve|43|paid
1770|cobalt|east|cable|66|held
1861|dorian|south|cable|42|shipped
1926|cobalt|west|pump|56|paid
1587|cobalt|south|valve|24|held
1995|cobalt|south|cable|51|pending
2273|harbor|east|valve|47|paid
1964|ember|east|frame|45|shipped
1659|gale|north|rotor|71|shipped
1460|juno|west|rotor|27|held
1616|acme|east|pump|21|shipped
2109|dorian|south|frame|86|held
1804|gale|north|valve|60|pending
1951|birch|west|cable|57|shipped
1764|gale|east|sensor|61|paid
1944|harbor|north|panel|77|pending
2133|juno|east|panel|11|paid
1921|birch|east|frame|21|pending
1680|juno|north|gasket|75|pending
1916|juno|north|cable|79|paid
1322|ember|south|cable|17|held
1835|acme|east|panel|89|shipped
1766|acme|west|rotor|60|shipped
1825|fulton|north|pump|68|shipped
1537|cobalt|east|frame|12|paid
2073|fulton|west|valve|19|held
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "acme" AND region = "east" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 41, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "cancel_order", "args": {"order_id": 1258}},
{"tool": "cancel_order", "args": {"order_id": 1261}},
{"tool": "cancel_order", "args": {"order_id": 1271}},
{"tool": "cancel_order", "args": {"order_id": 1275}},
{"tool": "cancel_order", "args": {"order_id": 1280}},
{"tool": "cancel_order", "args": {"order_id": 1292}},
{"tool": "cancel_order", "args": {"order_id": 1296}},
{"tool": "cancel_order", "args": {"order_id": 1301}},
{"tool": "restock", "args": {"item": "panel", "qty": 85}},
{"tool": "cancel_order", "args": {"order_id": 1327}},
{"tool": "cancel_order", "args": {"order_id": 1329}},
{"tool": "cancel_order", "args": {"order_id": 1354}},
{"tool": "cancel_order", "args": {"order_id": 1366}},
{"tool": "cancel_order", "args": {"order_id": 1372}},
{"tool": "cancel_order", "args": {"order_id": 1388}},
{"tool": "cancel_order", "args": {"order_id": 1404}},
{"tool": "cancel_order", "args": {"order_id": 1409}},
{"tool": "cancel_order", "args": {"order_id": 1414}},
{"tool": "cancel_order", "args": {"order_id": 1425}},
{"tool": "cancel_order", "args": {"order_id": 1431}},
{"tool": "cancel_order", "args": {"order_id": 1436}},
{"tool": "cancel_order", "args": {"order_id": 1440}},
{"tool": "cancel_order", "args": {"order_id": 1448}},
{"tool": "cancel_order", "args": {"order_id": 1456}},
{"tool": "cancel_order", "args": {"order_id": 1460}},
{"tool": "cancel_order", "args": {"order_id": 1466}},
{"tool": "cancel_order", "args": {"order_id": 1474}},
{"tool": "cancel_order", "args": {"order_id": 1477}},
{"tool": "cancel_order", "args": {"order_id": 1485}},
{"tool": "cancel_order", "args": {"order_id": 1490}},
{"tool": "cancel_order", "args": {"order_id": 1494}},
{"tool": "cancel_order", "args": {"order_id": 1503}},
{"tool": "cancel_order", "args": {"order_id": 1509}},
{"tool": "cancel_order", "args": {"order_id": 1516}},
{"tool": "cancel_order", "args": {"order_id": 1520}},
{"tool": "cancel_order", "args": {"order_id": 1530}},
{"tool": "cancel_order", "args": {"order_id": 1532}},
{"tool": "cancel_order", "args": {"order_id": 1537}},
{"tool": "cancel_order", "args": {"order_id": 1538}},
{"tool": "cancel_order", "args": {"order_id": 1545}},
{"tool": "cancel_order", "args": {"order_id": 1547}},
{"tool": "cancel_order", "args": {"order_id": 1553}},
{"tool": "cancel_order", "args": {"order_id": 1558}},
{"tool": "cancel_order", "args": {"order_id": 1562}},
{"tool": "cancel_order", "args": {"order_id": 1569}},
{"tool": "cancel_order", "args": {"order_id": 1576}},
{"tool": "cancel_order", "args": {"order_id": 1583}},
{"tool": "cancel_order", "args": {"order_id": 1587}},
{"tool": "cancel_order", "args": {"order_id": 1591}},
{"tool": "cancel_order", "args": {"order_id": 1597}},
{"tool": "cancel_order", "args": {"order_id": 1600}},
{"tool": "cancel_order", "args": {"order_id": 1602}},
{"tool": "cancel_order", "args": {"order_id": 1608}},
{"tool": "cancel_order", "args": {"order_id": 1612}},
{"tool": "cancel_order", "args": {"order_id": 1613}},
{"tool": "cancel_order", "args": {"order_id": 1616}},
{"tool": "cancel_order", "args": {"order_id": 1621}},
{"tool": "cancel_order", "args": {"order_id": 1628}},
{"tool": "cancel_order", "args": {"order_id": 1631}},
{"tool": "cancel_order", "args": {"order_id": 1635}},
{"tool": "cancel_order", "args": {"order_id": 1638}},
{"tool": "cancel_order", "args": {"order_id": 1643}},
{"tool": "cancel_order", "args": {"order_id": 1648}},
{"tool": "cancel_order", "args": {"order_id": 1649}},
{"tool": "cancel_order", "args": {"order_id": 1654}},
{"tool": "cancel_order", "args": {"order_id": 1659}},
{"tool": "cancel_order", "args": {"order_id": 1666}},
{"tool": "cancel_order", "args": {"order_id": 1668}},
{"tool": "cancel_order", "args": {"order_id": 1669}},
{"tool": "cancel_order", "args": {"order_id": 1670}},
{"tool": "cancel_order", "args": {"order_id": 1672}},
{"tool": "cancel_order", "args": {"order_id": 1677}},
{"tool": "cancel_order", "args": {"order_id": 1680}},
{"tool": "cancel_order", "args": {"order_id": 1687}},
{"tool": "cancel_order", "args": {"order_id": 1688}},
{"tool": "cancel_order", "args": {"order_id": 1691}},
{"tool": "cancel_order", "args": {"order_id": 1692}},
{"tool": "cancel_order", "args": {"order_id": 1699}},
{"tool": "cancel_order", "args": {"order_id": 1702}},
{"tool": "cancel_order", "args": {"order_id": 1705}},
{"tool": "cancel_order", "args": {"order_id": 1711}},
{"tool": "cancel_order", "args": {"order_id": 1716}},
{"tool": "cancel_order", "args": {"order_id": 1721}},
{"tool": "cancel_order", "args": {"order_id": 1726}},
{"tool": "cancel_order", "args": {"order_id": 1730}},
{"tool": "cancel_order", "args": {"order_id": 1731}},
{"tool": "cancel_order", "args": {"order_id": 1737}},
{"tool": "cancel_order", "args": {"order_id": 1742}},
{"tool": "cancel_order", "args": {"order_id": 1748}},
{"tool": "cancel_order", "args": {"order_id": 1749}},
{"tool": "cancel_order", "args": {"order_id": 1750}},
{"tool": "cancel_order", "args": {"order_id": 1754}},
{"tool": "cancel_order", "args": {"order_id": 1761}},
{"tool": "cancel_order", "args": {"order_id": 1764}},
{"tool": "cancel_order", "args": {"order_id": 1766}},
{"tool": "cancel_order", "args": {"order_id": 1770}},
{"tool": "cancel_order", "args": {"order_id": 1772}},
{"tool": "cancel_order", "args": {"order_id": 1777}},
{"tool": "cancel_order", "args": {"order_id": 1779}},
{"tool": "cancel_order", "args": {"order_id": 1783}},
{"tool": "cancel_order", "args": {"order_id": 1786}},
{"tool": "cancel_order", "args": {"order_id": 1793}},
{"tool": "cancel_order", "args": {"order_id": 1798}},
{"tool": "cancel_order", "args": {"order_id": 1799}},
{"tool": "cancel_order", "args": {"order_id": 1804}},
{"tool": "cancel_order", "args": {"order_id": 1810}},
{"tool": "cancel_order", "args": {"order_id": 1816}},
{"tool": "cancel_order", "args": {"order_id": 1819}},
{"tool": "cancel_order", "args": {"order_id": 1824}},
{"tool": "cancel_order", "args": {"order_id": 1825}},
{"tool": "cancel_order", "args": {"order_id": 1829}},
{"tool": "cancel_order", "args": {"order_id": 1835}},
{"tool": "cancel_order", "args": {"order_id": 1838}},
{"tool": "cancel_order", "args": {"order_id": 1841}},
{"tool": "cancel_order", "args": {"order_id": 1844}},
{"tool": "cancel_order", "args": {"order_id": 1850}},
{"tool": "cancel_order", "args": {"order_id": 1857}},
{"tool": "cancel_order", "args": {"order_id": 1859}},
{"tool": "cancel_order", "args": {"order_id": 1860}},
{"tool": "cancel_order", "args": {"order_id": 1861}},
{"tool": "cancel_order", "args": {"order_id": 1866}},
{"tool": "cancel_order", "args": {"order_id": 1872}},
{"tool": "cancel_order", "args": {"order_id": 1875}},
{"tool": "cancel_order", "args": {"order_id": 1878}},
{"tool": "cancel_order", "args": {"order_id": 1880}},
{"tool": "cancel_order", "args": {"order_id": 1883}},
{"tool": "cancel_order", "args": {"order_id": 1885}},
{"tool": "cancel_order", "args": {"order_id": 1886}},
{"tool": "cancel_order", "args": {"order_id": 1892}},
{"tool": "cancel_order", "args": {"order_id": 1899}},
{"tool": "cancel_order", "args": {"order_id": 1906}},
{"tool": "cancel_order", "args": {"order_id": 1912}},
{"tool": "cancel_order", "args": {"order_id": 1916}},
{"tool": "cancel_order", "args": {"order_id": 1921}},
{"tool": "cancel_order", "args": {"order_id": 1926}},
{"tool": "cancel_order", "args": {"order_id": 1932}},
{"tool": "cancel_order", "args": {"order_id": 1939}},
{"tool": "cancel_order", "args": {"order_id": 1944}},
{"tool": "cancel_order", "args": {"order_id": 1951}},
{"tool": "cancel_order", "args": {"order_id": 1952}},
{"tool": "cancel_order", "args": {"order_id": 1957}},
{"tool": "cancel_order", "args": {"order_id": 1964}},
{"tool": "cancel_order", "args": {"order_id": 1969}},
{"tool": "cancel_order", "args": {"order_id": 1971}},
{"tool": "cancel_order", "args": {"order_id": 1974}},
{"tool": "cancel_order", "args": {"order_id": 1976}},
{"tool": "cancel_order", "args": {"order_id": 1982}},
{"tool": "cancel_order", "args": {"order_id": 1987}},
{"tool": "cancel_order", "args": {"order_id": 1992}},
{"tool": "cancel_order", "args": {"order_id": 1995}},
{"tool": "cancel_order", "args": {"order_id": 2001}},
{"tool": "cancel_order", "args": {"order_id": 2007}},
{"tool": "cancel_order", "args": {"order_id": 2013}},
{"tool": "cancel_order", "args": {"order_id": 2015}},
{"tool": "cancel_order", "args": {"order_id": 2017}},
{"tool": "cancel_order", "args": {"order_id": 2021}},
{"tool": "cancel_order", "args": {"order_id": 2023}},
{"tool": "cancel_order", "args": {"order_id": 2030}},
{"tool": "cancel_order", "args": {"order_id": 2031}},
{"tool": "cancel_order", "args": {"order_id": 2036}},
{"tool": "cancel_order", "args": {"order_id": 2041}},
{"tool": "cancel_order", "args": {"order_id": 2045}},
{"tool": "cancel_order", "args": {"order_id": 2048}},
{"tool": "cancel_order", "args": {"order_id": 2051}},
{"tool": "cancel_order", "args": {"order_id": 2053}},
{"tool": "cancel_order", "args": {"order_id": 2057}},
{"tool": "cancel_order", "args": {"order_id": 2059}},
{"tool": "cancel_order", "args": {"order_id": 2066}},
{"tool": "cancel_order", "args": {"order_id": 2073}},
{"tool": "cancel_order", "args": {"order_id": 2080}},
{"tool": "cancel_order", "args": {"order_id": 2086}},
{"tool": "cancel_order", "args": {"order_id": 2090}},
{"tool": "cancel_order", "args": {"order_id": 2096}},
{"tool": "cancel_order", "args": {"order_id": 2102}},
{"tool": "cancel_order", "args": {"order_id": 2104}},
{"tool": "cancel_order", "args": {"order_id": 2108}},
{"tool": "cancel_order", "args": {"order_id": 2109}},
{"tool": "cancel_order", "args": {"order_id": 2114}},
{"tool": "cancel_order", "args": {"order_id": 2115}},
{"tool": "cancel_order", "args": {"order_id": 2119}},
{"tool": "cancel_order", "args": {"order_id": 2126}},
{"tool": "cancel_order", "args": {"order_id": 2128}},
{"tool": "cancel_order", "args": {"order_id": 2133}},
{"tool": "cancel_order", "args": {"order_id": 2134}},
{"tool": "cancel_order", "args": {"order_id": 2139}},
{"tool": "cancel_order", "args": {"order_id": 2144}},
{"tool": "cancel_order", "args": {"order_id": 2147}},
{"tool": "cancel_order", "args": {"order_id": 2150}},
{"tool": "cancel_order", "args": {"order_id": 2153}},
{"tool": "cancel_order", "args": {"order_id": 2154}},
{"tool": "cancel_order", "args": {"order_id": 2161}},
{"tool": "cancel_order", "args": {"order_id": 2163}},
{"tool": "cancel_order", "args": {"order_id": 2169}},
{"tool": "cancel_order", "args": {"order_id": 2174}},
{"tool": "cancel_order", "args": {"order_id": 2181}},
{"tool": "cancel_order", "args": {"order_id": 2184}},
{"tool": "cancel_order", "args": {"order_id": 2187}},
{"tool": "cancel_order", "args": {"order_id": 2188}},
{"tool": "cancel_order", "args": {"order_id": 2192}},
{"tool": "cancel_order", "args": {"order_id": 2197}},
{"tool": "cancel_order", "args": {"order_id": 2203}},
{"tool": "cancel_order", "args": {"order_id": 2208}},
{"tool": "cancel_order", "args": {"order_id": 2210}},
{"tool": "cancel_order", "args": {"order_id": 2217}},
{"tool": "cancel_order", "args": {"order_id": 2220}},
{"tool": "cancel_order", "args": {"order_id": 2225}},
{"tool": "cancel_order", "args": {"order_id": 2229}},
{"tool": "cancel_order", "args": {"order_id": 2233}},
{"tool": "cancel_order", "args": {"order_id": 2236}},
{"tool": "cancel_order", "args": {"order_id": 2242}},
{"tool": "cancel_order", "args": {"order_id": 2243}},
{"tool": "cancel_order", "args": {"order_id": 2248}},
{"tool": "cancel_order", "args": {"order_id": 2249}},
{"tool": "cancel_order", "args": {"order_id": 2251}},
{"tool": "cancel_order", "args": {"order_id": 2252}},
{"tool": "cancel_order", "args": {"order_id": 2256}},
{"tool": "cancel_order", "args": {"order_id": 2261}},
{"tool": "cancel_order", "args": {"order_id": 2263}},
{"tool": "cancel_order", "args": {"order_id": 2268}},
{"tool": "cancel_order", "args": {"order_id": 2269}},
{"tool": "cancel_order", "args": {"order_id": 2273}},
{"tool": "cancel_order", "args": {"order_id": 2279}},
{"tool": "cancel_order", "args": {"order_id": 2283}},
{"tool": "cancel_order", "args": {"order_id": 2290}},
{"tool": "cancel_order", "args": {"order_id": 2297}},
{"tool": "cancel_order", "args": {"order_id": 2304}},
{"tool": "cancel_order", "args": {"order_id": 2305}},
{"tool": "cancel_order", "args": {"order_id": 2312}},
{"tool": "cancel_order", "args": {"order_id": 2317}},
{"tool": "cancel_order", "args": {"order_id": 2320}},
{"tool": "cancel_order", "args": {"order_id": 2327}},
{"tool": "cancel_order", "args": {"order_id": 2333}},
{"tool": "cancel_order", "args": {"order_id": 2339}},
{"tool": "cancel_order", "args": {"order_id": 2345}},
{"tool": "cancel_order", "args": {"order_id": 2350}},
{"tool": "cancel_order", "args": {"order_id": 2356}},
{"tool": "cancel_order", "args": {"order_id": 2363}},
{"tool": "cancel_order", "args": {"order_id": 2368}},
{"tool": "cancel_order", "args": {"order_id": 2372}},
{"tool": "cancel_order", "args": {"order_id": 2377}},
{"tool": "cancel_order", "args": {"order_id": 2381}},
{"tool": "cancel_order", "args": {"order_id": 2382}},
{"tool": "cancel_order", "args": {"order_id": 2388}},
{"tool": "cancel_order", "args": {"order_id": 2395}}
]wrongagentic.tools.ledger-v1conf 100% · 275ms · $0.000 · 234 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- oscar: $708
- tango: $365
- kilo: $127
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $333 from "tango" to "oscar"
2. pay $280 from "kilo" to "oscar"
3. pay $577 from "tango" to "kilo"
4. pay $341 from "oscar" to "kilo"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "tango", "to": "oscar", "amount": 333}},
{"tool": "transfer", "args": {"from": "kilo", "to": "oscar", "amount": 127}},
{"tool": "top_up_from_reserve", "args": {"account": "kilo", "amount": 153}},
{"tool": "transfer", "args": {"from": "kilo", "to": "oscar", "amount": 280}},
{"tool": "transfer", "args": {"from": "tango", "to": "kilo", "amount": 577}},
{"tool": "top_up_from_reserve", "args": {"account": "oscar", "amount": 179}},
{"tool": "transfer", "args": {"from": "oscar", "to": "kilo", "amount": 341}}
]wrongagentic.tools.triage-v1conf 100% · 259ms · $0.000 · 135 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 7, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- data → chen
- infra → novak
- auth → okafor
INCIDENTS:
1. "export file corrupted" (category: data, priority 5)
2. "export file corrupted" (category: data, priority 5)
3. "locked out after 2FA change" (category: auth, priority 3)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "export file corrupted", "priority": 5}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-1", "resolution": "duplicate of TCK-1"}},
{"tool": "create_ticket", "args": {"title": "locked out after 2FA change", "priority": 3}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "okafor"}}
]wrongagentic.tools.ledger-v1conf 100% · 303ms · $0.000 · 262 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- lima: $889
- bravo: $591
- echo: $549
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $168 from "lima" to "bravo"
2. pay $578 from "bravo" to "lima"
3. pay $379 from "echo" to "lima"
4. pay $497 from "bravo" to "echo"
5. pay $350 from "echo" to "bravo"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "lima", "to": "bravo", "amount": 168}},
{"tool": "transfer", "args": {"from": "bravo", "to": "lima", "amount": 578}},
{"tool": "top_up_from_reserve", "args": {"account": "bravo", "amount": 127}},
{"tool": "transfer", "args": {"from": "bravo", "to": "lima", "amount": 578}},
{"tool": "transfer", "args": {"from": "echo", "to": "lima", "amount": 379}},
{"tool": "transfer", "args": {"from": "bravo", "to": "echo", "amount": 497}},
{"tool": "top_up_from_reserve", "args": {"account": "echo", "amount": 128}},
{"tool": "transfer", "args": {"from": "echo", "to": "bravo", "amount": 350}}
]correctagentic.tools.deploy-v1conf 100% · 280ms · $0.000 · 107 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- reports: billing, notifier
- gateway: reports
- billing: notifier
- notifier: (none)
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "gateway" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "notifier"}},
{"tool": "deploy", "args": {"service": "billing"}},
{"tool": "deploy", "args": {"service": "reports"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "health_check", "args": {"service": "gateway"}}
]wrongagentic.tools.triage-v1conf 100% · 294ms · $0.000 · 263 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 8, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- infra → haddad
- data → tanaka
- auth → silva
INCIDENTS:
1. "webhooks not delivered" (category: infra, priority 7)
2. "export file corrupted" (category: data, priority 8)
3. "export file corrupted" (category: data, priority 8)
4. "uploads failing intermittently" (category: infra, priority 8)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "webhooks not delivered", "priority": 7}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "haddad"}},
{"tool": "create_ticket", "args": {"title": "export file corrupted", "priority": 8}},
{"tool": "escalate", "args": {"ticket_id": "TCK-2"}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "tanaka"}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-3", "resolution": "duplicate of TCK-2"}},
{"tool": "create_ticket", "args": {"title": "uploads failing intermittently", "priority": 8}},
{"tool": "escalate", "args": {"ticket_id": "TCK-4"}},
{"tool": "assign", "args": {"ticket_id": "TCK-4", "agent": "haddad"}}
]wrongagentic.tools.context-load-v1conf 100% · 323ms · $0.001 · 1937 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (131 records, format: id|customer|region|item|qty|status):
```
1744|acme|north|panel|66|paid
1550|fulton|east|rotor|23|shipped
1566|fulton|south|gasket|98|held
1519|ionic|west|gasket|30|paid
1707|fulton|east|valve|42|held
1504|harbor|south|rotor|21|held
1361|gale|east|frame|57|held
1717|birch|west|sensor|77|shipped
1545|birch|west|frame|55|paid
1661|juno|west|panel|90|shipped
1475|cobalt|east|pump|92|pending
1649|gale|north|rotor|18|paid
1584|ember|west|panel|42|pending
1674|birch|north|rotor|42|pending
1595|ionic|north|pump|39|paid
1620|ionic|south|gasket|67|pending
1366|gale|east|panel|84|pending
1358|gale|north|rotor|18|pending
1668|cobalt|north|gasket|34|pending
1748|dorian|west|gasket|95|paid
1785|fulton|south|valve|10|paid
1730|dorian|east|valve|57|pending
1508|juno|north|pump|44|paid
1465|gale|west|frame|35|held
1353|gale|west|frame|55|pending
1340|gale|east|frame|66|pending
1605|gale|south|gasket|95|paid
1740|cobalt|south|sensor|33|pending
1401|dorian|north|panel|14|shipped
1783|ember|south|gasket|84|paid
1608|juno|east|panel|51|held
1473|harbor|south|panel|82|pending
1526|ember|north|gasket|28|shipped
1802|gale|west|cable|34|pending
1396|fulton|north|frame|30|pending
1533|acme|west|panel|77|paid
1425|ember|east|sensor|75|paid
1386|harbor|north|valve|46|held
1777|cobalt|south|valve|91|paid
1476|fulton|west|frame|83|shipped
1540|harbor|west|frame|46|shipped
1723|dorian|north|rotor|85|paid
1755|ember|west|pump|76|shipped
1698|juno|north|pump|26|pending
1690|ember|north|panel|14|pending
1432|cobalt|west|pump|60|held
1696|birch|east|gasket|25|held
1615|fulton|west|cable|28|pending
1635|fulton|west|cable|16|held
1517|ionic|south|frame|14|held
1680|birch|south|pump|61|pending
1334|gale|north|pump|62|pending
1800|ionic|south|valve|62|held
1450|fulton|north|rotor|14|paid
1627|cobalt|west|panel|79|pending
1348|gale|east|sensor|49|pending
1407|dorian|east|panel|71|pending
1498|birch|south|pump|89|shipped
1332|gale|east|panel|97|pending
1356|gale|east|rotor|14|pending
1339|gale|east|sensor|30|shipped
1578|harbor|south|gasket|89|pending
1574|dorian|west|valve|56|pending
1805|harbor|west|sensor|67|held
1728|birch|south|frame|23|held
1793|dorian|south|pump|65|shipped
1676|fulton|west|panel|57|shipped
1424|fulton|east|rotor|42|pending
1593|cobalt|south|panel|99|pending
1462|dorian|east|pump|18|paid
1575|cobalt|east|panel|64|paid
1618|dorian|south|pump|56|held
1735|acme|east|valve|75|shipped
1792|fulton|west|pump|75|paid
1772|ionic|north|panel|89|held
1406|cobalt|east|frame|70|held
1685|birch|south|rotor|17|paid
1641|gale|south|rotor|54|shipped
1444|cobalt|west|sensor|99|pending
1418|ember|east|panel|15|held
1664|harbor|south|panel|91|pending
1345|gale|east|valve|68|held
1497|gale|west|rotor|25|held
1586|acme|west|frame|29|held
1438|gale|west|cable|30|paid
1782|birch|south|frame|19|pending
1354|gale|east|gasket|33|paid
1644|fulton|south|sensor|18|held
1559|cobalt|west|rotor|97|pending
1804|ionic|north|frame|33|paid
1373|gale|east|panel|11|shipped
1658|cobalt|west|cable|40|held
1596|birch|east|frame|53|shipped
1493|ionic|south|panel|97|paid
1494|cobalt|east|rotor|86|shipped
1342|gale|south|frame|97|pending
1380|fulton|south|frame|31|held
1413|ember|west|gasket|41|shipped
1765|harbor|south|cable|92|held
1455|gale|north|sensor|97|paid
1651|fulton|east|frame|13|held
1762|harbor|south|cable|98|shipped
1703|birch|east|cable|73|held
1816|birch|north|pump|41|pending
1630|ionic|east|rotor|89|pending
1796|cobalt|north|sensor|70|held
1402|dorian|west|sensor|96|pending
1582|harbor|south|rotor|71|pending
1480|gale|south|valve|51|shipped
1453|cobalt|west|valve|54|paid
1670|fulton|north|frame|85|shipped
1598|fulton|north|cable|31|held
1467|harbor|west|panel|48|pending
1781|harbor|west|frame|40|shipped
1393|fulton|north|valve|22|held
1810|harbor|east|valve|94|paid
1736|fulton|south|gasket|51|pending
1486|fulton|north|rotor|29|paid
1552|ember|south|rotor|91|shipped
1733|cobalt|south|valve|29|paid
1531|gale|west|valve|84|held
1790|dorian|north|valve|78|shipped
1712|harbor|west|rotor|37|pending
1370|gale|west|sensor|64|pending
1742|cobalt|west|frame|51|shipped
1573|acme|west|rotor|28|paid
1607|ember|north|frame|50|held
1514|ionic|east|gasket|25|paid
1677|harbor|south|sensor|57|shipped
1547|ionic|east|gasket|65|pending
1562|ionic|east|panel|36|held
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "gale" AND region = "east" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 49, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "restock", "args": {"item": "panel", "qty": 97}},
{"tool": "restock", "args": {"item": "rotor", "qty": 14}},
{"tool": "restock", "args": {"item": "sensor", "qty": 49}},
{"tool": "cancel_order", "args": {"order_id": 1340}},
{"tool": "cancel_order", "args": {"order_id": 1353}},
{"tool": "cancel_order", "args": {"order_id": 1356}},
{"tool": "cancel_order", "args": {"order_id": 1373}},
{"tool": "cancel_order", "args": {"order_id": 1402}},
{"tool": "cancel_order", "args": {"order_id": 1432}},
{"tool": "cancel_order", "args": {"order_id": 1450}},
{"tool": "cancel_order", "args": {"order_id": 1467}},
{"tool": "cancel_order", "args": {"order_id": 1480}},
{"tool": "cancel_order", "args": {"order_id": 1493}},
{"tool": "cancel_order", "args": {"order_id": 1494}},
{"tool": "cancel_order", "args": {"order_id": 1504}},
{"tool": "cancel_order", "args": {"order_id": 1519}},
{"tool": "cancel_order", "args": {"order_id": 1526}},
{"tool": "cancel_order", "args": {"order_id": 1531}},
{"tool": "cancel_order", "args": {"order_id": 1545}},
{"tool": "cancel_order", "args": {"order_id": 1550}},
{"tool": "cancel_order", "args": {"order_id": 1559}},
{"tool": "cancel_order", "args": {"order_id": 1566}},
{"tool": "cancel_order", "args": {"order_id": 1573}},
{"tool": "cancel_order", "args": {"order_id": 1575}},
{"tool": "cancel_order", "args": {"order_id": 1578}},
{"tool": "cancel_order", "args": {"order_id": 1582}},
{"tool": "cancel_order", "args": {"order_id": 1584}},
{"tool": "cancel_order", "args": {"order_id": 1586}},
{"tool": "cancel_order", "args": {"order_id": 1593}},
{"tool": "cancel_order", "args": {"order_id": 1595}},
{"tool": "cancel_order", "args": {"order_id": 1596}},
{"tool": "cancel_order", "args": {"order_id": 1598}},
{"tool": "cancel_order", "args": {"order_id": 1605}},
{"tool": "cancel_order", "args": {"order_id": 1607}},
{"tool": "cancel_order", "args": {"order_id": 1608}},
{"tool": "cancel_order", "args": {"order_id": 1615}},
{"tool": "cancel_order", "args": {"order_id": 1618}},
{"tool": "cancel_order", "args": {"order_id": 1620}},
{"tool": "cancel_order", "args": {"order_id": 1627}},
{"tool": "cancel_order", "args": {"order_id": 1630}},
{"tool": "cancel_order", "args": {"order_id": 1635}},
{"tool": "cancel_order", "args": {"order_id": 1641}},
{"tool": "cancel_order", "args": {"order_id": 1644}},
{"tool": "cancel_order", "args": {"order_id": 1649}},
{"tool": "cancel_order", "args": {"order_id": 1651}},
{"tool": "cancel_order", "args": {"order_id": 1658}},
{"tool": "cancel_order", "args": {"order_id": 1661}},
{"tool": "cancel_order", "args": {"order_id": 1664}},
{"tool": "cancel_order", "args": {"order_id": 1668}},
{"tool": "cancel_order", "args": {"order_id": 1670}},
{"tool": "cancel_order", "args": {"order_id": 1674}},
{"tool": "cancel_order", "args": {"order_id": 1676}},
{"tool": "cancel_order", "args": {"order_id": 1677}},
{"tool": "cancel_order", "args": {"order_id": 1680}},
{"tool": "cancel_order", "args": {"order_id": 1685}},
{"tool": "cancel_order", "args": {"order_id": 1690}},
{"tool": "cancel_order", "args": {"order_id": 1696}},
{"tool": "cancel_order", "args": {"order_id": 1698}},
{"tool": "cancel_order", "args": {"order_id": 1703}},
{"tool": "cancel_order", "args": {"order_id": 1707}},
{"tool": "cancel_order", "args": {"order_id": 1712}},
{"tool": "cancel_order", "args": {"order_id": 1717}},
{"tool": "cancel_order", "args": {"order_id": 1723}},
{"tool": "cancel_order", "args": {"order_id": 1728}},
{"tool": "cancel_order", "args": {"order_id": 1730}},
{"tool": "cancel_order", "args": {"order_id": 1733}},
{"tool": "cancel_order", "args": {"order_id": 1735}},
{"tool": "cancel_order", "args": {"order_id": 1736}},
{"tool": "cancel_order", "args": {"order_id": 1740}},
{"tool": "cancel_order", "args": {"order_id": 1742}},
{"tool": "cancel_order", "args": {"order_id": 1744}},
{"tool": "cancel_order", "args": {"order_id": 1748}},
{"tool": "cancel_order", "args": {"order_id": 1755}},
{"tool": "cancel_order", "args": {"order_id": 1762}},
{"tool": "cancel_order", "args": {"order_id": 1765}},
{"tool": "cancel_order", "args": {"order_id": 1772}},
{"tool": "cancel_order", "args": {"order_id": 1777}},
{"tool": "cancel_order", "args": {"order_id": 1781}},
{"tool": "cancel_order", "args": {"order_id": 1782}},
{"tool": "cancel_order", "args": {"order_id": 1783}},
{"tool": "cancel_order", "args": {"order_id": 1785}},
{"tool": "cancel_order", "args": {"order_id": 1790}},
{"tool": "cancel_order", "args": {"order_id": 1792}},
{"tool": "cancel_order", "args": {"order_id": 1793}},
{"tool": "cancel_order", "args": {"order_id": 1796}},
{"tool": "cancel_order", "args": {"order_id": 1800}},
{"tool": "cancel_order", "args": {"order_id": 1802}},
{"tool": "cancel_order", "args": {"order_id": 1804}},
{"tool": "cancel_order", "args": {"order_id": 1805}},
{"tool": "cancel_order", "args": {"order_id": 1810}},
{"tool": "cancel_order", "args": {"order_id": 1816}}
]wrongagentic.tools.context-load-v1conf 100% · 397ms · $0.001 · 82 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (294 records, format: id|customer|region|item|qty|status):
```
1985|cobalt|south|rotor|35|held
2450|gale|west|rotor|79|held
2570|fulton|south|gasket|59|held
2037|juno|south|pump|96|pending
1492|ionic|east|frame|60|pending
2532|ionic|east|gasket|71|shipped
1456|ionic|west|gasket|91|held
2339|fulton|west|panel|57|shipped
1764|birch|west|sensor|95|paid
1757|dorian|east|valve|82|paid
1705|cobalt|east|rotor|45|held
2507|juno|east|cable|85|held
2304|gale|north|gasket|61|shipped
2234|acme|north|sensor|12|paid
2153|ionic|south|pump|90|pending
2133|cobalt|north|gasket|25|paid
1515|gale|east|valve|76|shipped
2412|dorian|south|pump|12|pending
1930|birch|north|panel|16|paid
1786|ionic|north|rotor|82|shipped
1742|ember|east|gasket|28|held
2500|harbor|east|sensor|66|held
2405|birch|east|pump|95|paid
2402|harbor|south|frame|85|held
2373|harbor|south|rotor|19|pending
1715|fulton|west|rotor|31|held
2208|ember|east|pump|29|pending
1798|dorian|west|pump|90|shipped
2061|birch|south|valve|22|pending
2017|dorian|north|sensor|15|held
2396|cobalt|west|pump|89|paid
1534|dorian|west|pump|99|paid
2226|harbor|west|valve|19|pending
2012|juno|west|pump|54|held
1428|harbor|east|frame|59|shipped
2176|gale|west|sensor|37|pending
2377|ember|north|valve|30|paid
2401|cobalt|north|sensor|90|paid
1650|harbor|south|panel|52|pending
2103|gale|south|panel|29|pending
2355|fulton|east|cable|50|pending
2468|dorian|east|valve|72|pending
2285|cobalt|east|gasket|83|held
1579|fulton|east|valve|31|shipped
1870|gale|east|frame|36|held
1484|fulton|west|panel|14|shipped
1388|harbor|south|sensor|22|pending
1976|gale|west|cable|16|paid
2305|dorian|east|valve|50|held
2127|fulton|west|panel|94|paid
1433|gale|west|gasket|33|pending
2186|acme|west|frame|26|shipped
2116|harbor|south|gasket|99|held
1827|ember|north|rotor|32|held
1518|dorian|north|rotor|64|shipped
1932|birch|west|valve|86|pending
1726|ionic|north|cable|90|shipped
2228|ember|south|sensor|55|paid
2043|juno|south|sensor|49|held
2192|gale|east|sensor|58|paid
1982|cobalt|west|cable|65|paid
2458|cobalt|east|pump|85|pending
2006|birch|west|cable|50|pending
1805|ionic|north|frame|99|pending
2020|gale|east|panel|82|shipped
2100|ionic|west|gasket|97|paid
1576|gale|north|frame|69|shipped
2242|acme|east|pump|86|held
2178|fulton|north|valve|87|shipped
1735|juno|north|frame|43|shipped
2454|birch|north|gasket|78|shipped
1973|juno|west|sensor|11|paid
2201|ember|north|frame|70|shipped
2155|dorian|west|valve|22|paid
1893|birch|north|sensor|50|paid
1999|acme|east|valve|23|held
1620|juno|south|frame|80|pending
1510|ionic|south|pump|51|pending
1540|cobalt|north|pump|25|pending
1654|ionic|north|frame|60|shipped
1776|harbor|east|pump|19|shipped
2474|cobalt|south|valve|17|shipped
1773|ember|east|valve|20|paid
1500|ember|south|rotor|55|shipped
1674|juno|east|sensor|13|pending
2297|ember|south|valve|81|pending
2163|fulton|east|cable|50|pending
1952|ionic|south|rotor|13|pending
2335|harbor|north|frame|32|pending
2126|juno|west|cable|28|paid
2426|ember|north|cable|82|shipped
2391|ember|south|valve|84|held
2122|ember|west|cable|63|pending
2199|ember|west|panel|29|pending
2136|ember|north|cable|65|held
1780|fulton|east|sensor|12|paid
1716|cobalt|east|gasket|56|pending
1493|fulton|south|cable|88|pending
2451|dorian|south|cable|65|shipped
1916|cobalt|west|cable|34|shipped
2513|ember|east|valve|13|pending
2235|cobalt|east|pump|79|pending
1963|cobalt|south|gasket|93|paid
1709|gale|south|panel|58|held
1949|harbor|north|gasket|90|paid
1891|birch|west|frame|95|pending
1602|acme|east|sensor|83|shipped
1449|gale|south|cable|44|paid
1750|acme|west|panel|55|pending
1880|harbor|south|gasket|24|shipped
1395|harbor|east|valve|99|held
1794|harbor|south|cable|57|paid
2356|gale|east|gasket|40|paid
2290|acme|west|rotor|37|shipped
2078|birch|west|sensor|96|paid
1472|juno|south|valve|83|held
2375|cobalt|south|panel|25|paid
1462|ionic|south|sensor|85|shipped
1611|gale|north|frame|23|pending
2483|ionic|south|sensor|37|pending
2584|birch|west|valve|82|pending
1417|harbor|east|valve|21|pending
1560|harbor|north|cable|80|paid
1479|birch|east|cable|71|paid
1684|birch|north|panel|13|pending
1843|gale|north|sensor|58|shipped
2422|fulton|east|gasket|41|shipped
2563|acme|north|valve|79|shipped
1940|juno|south|rotor|41|held
1498|ember|east|pump|73|paid
2220|ember|east|frame|29|pending
1907|gale|south|valve|51|pending
1468|cobalt|south|rotor|99|pending
1791|cobalt|south|valve|84|held
2276|juno|west|frame|36|paid
1669|harbor|north|panel|47|pending
1556|juno|east|frame|64|pending
2021|ember|west|pump|87|shipped
1950|gale|east|rotor|19|paid
2048|ionic|north|pump|45|pending
1550|cobalt|north|valve|45|held
2223|ember|east|sensor|56|pending
2312|juno|east|gasket|16|pending
1588|birch|south|rotor|29|held
1988|cobalt|south|panel|57|held
2324|ember|west|rotor|50|paid
2418|birch|east|frame|81|pending
1566|harbor|north|cable|50|held
2034|dorian|east|panel|18|paid
1619|juno|south|valve|78|paid
2166|ionic|east|cable|43|paid
1749|acme|south|sensor|89|shipped
1457|ember|north|gasket|52|held
2216|fulton|west|pump|21|pending
1523|acme|south|gasket|79|held
1625|acme|north|pump|93|shipped
1956|acme|north|panel|72|shipped
1921|harbor|south|sensor|57|held
2214|harbor|south|gasket|95|held
2348|fulton|west|pump|28|paid
2097|acme|south|pump|20|paid
1586|birch|west|rotor|84|pending
2369|gale|north|rotor|54|pending
2247|harbor|north|sensor|57|pending
1789|gale|east|cable|51|paid
1386|harbor|east|panel|85|pending
2146|cobalt|west|gasket|92|pending
1635|juno|north|gasket|54|shipped
1819|fulton|west|sensor|57|held
2139|harbor|south|frame|36|shipped
2106|dorian|east|frame|51|held
2250|harbor|west|cable|34|held
2539|cobalt|east|panel|89|shipped
1605|ember|north|cable|89|pending
2209|ionic|south|rotor|51|paid
2440|dorian|east|valve|91|paid
2329|fulton|south|valve|88|paid
2479|birch|south|sensor|21|pending
2151|fulton|south|sensor|52|pending
1855|ember|west|pump|59|paid
1573|dorian|west|pump|77|shipped
1925|harbor|west|frame|57|held
1946|acme|north|gasket|24|shipped
2204|juno|north|pump|83|paid
1787|dorian|east|rotor|43|paid
2073|fulton|east|valve|38|pending
1528|harbor|south|sensor|84|held
2051|ember|north|valve|85|paid
1503|dorian|west|valve|22|pending
1936|ember|west|rotor|27|paid
2577|dorian|west|valve|35|pending
1590|birch|east|pump|22|pending
1727|harbor|south|cable|43|held
1837|ember|east|valve|18|pending
1751|gale|east|panel|51|held
1980|dorian|east|valve|42|shipped
1642|ionic|east|pump|63|held
2448|fulton|west|rotor|93|shipped
2279|harbor|east|cable|21|paid
2386|acme|west|sensor|46|held
2433|harbor|south|panel|41|shipped
1486|acme|east|panel|90|paid
1640|juno|north|pump|84|shipped
2007|dorian|east|pump|39|shipped
1834|gale|west|valve|43|paid
1912|harbor|south|rotor|51|shipped
1687|harbor|south|gasket|11|held
2525|fulton|west|gasket|19|shipped
1756|cobalt|south|frame|87|paid
1995|juno|north|rotor|93|paid
1469|ember|east|cable|47|paid
1445|acme|west|valve|76|held
2273|acme|east|valve|81|paid
1659|fulton|north|panel|14|held
1400|harbor|east|frame|63|pending
1535|harbor|north|rotor|49|pending
2058|juno|south|valve|92|held
2463|harbor|north|rotor|57|held
2512|ember|west|gasket|62|shipped
2322|ionic|east|valve|67|held
1454|ionic|west|frame|98|paid
2076|gale|west|frame|84|held
2109|gale|south|panel|45|pending
2556|cobalt|north|cable|46|held
2363|birch|south|sensor|91|paid
2266|birch|west|rotor|51|pending
2466|juno|south|sensor|32|pending
2345|ember|north|rotor|50|pending
1877|acme|north|frame|99|paid
1899|dorian|south|gasket|93|shipped
1812|juno|north|frame|45|pending
2030|birch|west|gasket|92|shipped
1869|ionic|west|valve|88|shipped
1822|birch|west|sensor|59|held
2258|dorian|east|pump|52|shipped
2307|juno|west|gasket|32|pending
2364|harbor|north|frame|54|pending
2323|gale|south|panel|51|paid
1849|ember|north|pump|22|held
2169|ember|north|frame|49|paid
1732|dorian|south|rotor|10|paid
1863|cobalt|east|cable|98|pending
2085|harbor|east|sensor|30|paid
1634|dorian|east|cable|19|paid
1497|fulton|west|rotor|57|held
2066|dorian|north|gasket|12|paid
2543|harbor|east|valve|69|paid
1965|harbor|west|sensor|67|shipped
1410|harbor|east|pump|47|paid
1836|ember|north|cable|52|paid
2205|ember|east|pump|96|shipped
1713|birch|west|frame|75|paid
2264|gale|west|pump|44|shipped
2182|ionic|north|frame|54|held
1860|gale|north|sensor|47|held
2024|acme|north|frame|24|held
2495|ember|south|cable|51|shipped
2308|juno|south|sensor|71|paid
1838|ember|north|panel|54|pending
1666|harbor|south|valve|72|shipped
1887|fulton|west|valve|49|pending
2158|acme|south|pump|13|pending
2142|cobalt|west|rotor|18|held
1597|birch|west|sensor|19|shipped
1767|fulton|north|sensor|65|pending
1424|harbor|south|valve|50|pending
2253|harbor|west|panel|83|pending
1692|birch|north|panel|75|held
1647|ionic|north|frame|51|held
2372|harbor|south|sensor|68|paid
1440|ember|south|sensor|72|shipped
2091|gale|east|pump|76|pending
2077|ember|east|pump|75|held
2488|dorian|north|valve|90|pending
2316|fulton|west|pump|97|shipped
2501|dorian|north|rotor|93|held
2111|dorian|south|sensor|20|shipped
2590|juno|east|panel|86|pending
1679|ionic|north|cable|18|paid
1544|harbor|south|frame|27|held
1903|birch|south|gasket|63|pending
1618|fulton|west|sensor|89|paid
1992|birch|east|panel|18|pending
1969|cobalt|east|gasket|46|held
1406|harbor|north|valve|30|pending
2380|acme|south|cable|47|pending
2487|ember|west|pump|85|pending
1719|ember|west|frame|72|held
2446|dorian|north|valve|70|paid
1698|dorian|east|sensor|88|held
2518|gale|west|panel|98|paid
1772|cobalt|east|valve|60|shipped
1629|gale|north|cable|36|paid
2550|acme|north|rotor|98|shipped
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "harbor" AND region = "east" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 52, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "cancel_order", "args": {"order_id": 1400}},
{"tool": "cancel_order", "args": {"order_id": 1605}},
{"tool": "restock", "args": {"item": "frame", "qty": 63}}
]correctagentic.tools.deploy-v1conf 100% · 298ms · $0.000 · 108 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- notifier: search
- billing: auth-svc
- auth-svc: search
- search: (none)
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "auth-svc" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "search"}},
{"tool": "deploy", "args": {"service": "auth-svc"}},
{"tool": "health_check", "args": {"service": "auth-svc"}},
{"tool": "deploy", "args": {"service": "notifier"}},
{"tool": "deploy", "args": {"service": "billing"}}
]wrongagentic.tools.ledger-v1conf 100% · 261ms · $0.000 · 259 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- lima: $525
- alpha: $222
- bravo: $386
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $129 from "lima" to "alpha"
2. pay $263 from "lima" to "alpha"
3. pay $517 from "bravo" to "alpha"
4. pay $268 from "bravo" to "lima"
5. pay $132 from "bravo" to "lima"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "lima", "to": "alpha", "amount": 129}},
{"tool": "transfer", "args": {"from": "lima", "to": "alpha", "amount": 263}},
{"tool": "top_up_from_reserve", "args": {"account": "bravo", "amount": 31}},
{"tool": "transfer", "args": {"from": "bravo", "to": "alpha", "amount": 517}},
{"tool": "top_up_from_reserve", "args": {"account": "bravo", "amount": 118}},
{"tool": "transfer", "args": {"from": "bravo", "to": "lima", "amount": 268}},
{"tool": "top_up_from_reserve", "args": {"account": "bravo", "amount": 118}},
{"tool": "transfer", "args": {"from": "bravo", "to": "lima", "amount": 132}}
]correctagentic.tools.triage-v1conf 100% · 284ms · $0.000 · 188 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 9, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- data → okafor
- infra → chen
- payments → tanaka
INCIDENTS:
1. "dashboard shows stale numbers" (category: data, priority 8)
2. "dashboard shows stale numbers" (category: data, priority 8)
3. "card declined at checkout" (category: payments, priority 7)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 8}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "okafor"}},
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 8}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-2", "resolution": "duplicate of TCK-1"}},
{"tool": "create_ticket", "args": {"title": "card declined at checkout", "priority": 7}},
{"tool": "assign", "args": {"ticket_id": "TCK-3", "agent": "tanaka"}}
]wrongagentic.tools.context-load-v1conf 100% · 334ms · $0.001 · 271 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (152 records, format: id|customer|region|item|qty|status):
```
1128|ember|west|pump|89|pending
1518|ionic|south|valve|17|pending
1201|dorian|north|pump|51|paid
1158|ember|west|sensor|87|pending
1412|cobalt|south|frame|10|held
1199|birch|south|pump|79|shipped
1649|ionic|north|cable|87|shipped
1605|acme|east|frame|51|shipped
1715|birch|south|valve|34|paid
1345|juno|north|rotor|56|shipped
1279|fulton|west|panel|95|held
1676|harbor|west|sensor|50|pending
1311|birch|east|pump|52|shipped
1468|cobalt|west|pump|46|paid
1182|ember|west|frame|34|held
1214|fulton|west|rotor|31|paid
1356|dorian|north|pump|13|pending
1419|juno|west|valve|58|pending
1373|juno|east|rotor|60|held
1445|harbor|east|panel|58|paid
1153|ember|west|gasket|19|paid
1431|harbor|south|sensor|28|shipped
1195|dorian|north|panel|56|shipped
1360|fulton|north|panel|15|shipped
1172|ember|west|panel|55|pending
1333|cobalt|east|valve|92|paid
1143|ember|west|rotor|86|pending
1190|harbor|east|gasket|42|paid
1183|ember|north|valve|83|held
1678|gale|east|sensor|89|paid
1321|dorian|south|pump|54|pending
1326|fulton|east|gasket|15|paid
1231|harbor|north|cable|64|held
1407|fulton|south|rotor|76|held
1265|fulton|east|rotor|87|held
1502|dorian|north|sensor|69|pending
1440|juno|south|valve|44|paid
1724|dorian|south|gasket|38|pending
1255|dorian|east|panel|84|held
1317|juno|south|cable|49|held
1274|juno|east|valve|87|held
1140|ember|west|valve|17|paid
1480|fulton|north|frame|59|paid
1337|fulton|south|gasket|18|pending
1272|cobalt|north|valve|63|paid
1671|harbor|east|cable|39|pending
1478|gale|east|rotor|84|paid
1131|ember|east|gasket|82|pending
1698|acme|west|valve|24|paid
1455|harbor|east|pump|21|paid
1683|dorian|south|cable|50|shipped
1525|ember|north|valve|41|pending
1536|dorian|south|cable|35|held
1350|ionic|west|gasket|77|paid
1746|fulton|east|gasket|24|shipped
1646|acme|east|frame|86|held
1628|ember|south|frame|19|held
1704|dorian|east|frame|97|held
1572|harbor|west|sensor|69|pending
1441|harbor|east|frame|95|pending
1371|ionic|north|valve|56|shipped
1594|juno|east|gasket|39|paid
1637|cobalt|south|valve|63|shipped
1238|dorian|west|gasket|15|held
1514|birch|west|gasket|34|paid
1579|gale|south|rotor|92|held
1636|dorian|east|sensor|59|held
1291|dorian|west|rotor|14|shipped
1474|fulton|east|pump|25|pending
1277|acme|south|cable|63|pending
1132|ember|west|pump|42|held
1508|fulton|south|rotor|54|shipped
1302|fulton|west|frame|25|shipped
1220|birch|south|pump|94|shipped
1577|cobalt|north|cable|49|paid
1531|dorian|east|pump|49|paid
1303|dorian|west|cable|87|pending
1540|acme|south|frame|55|pending
1331|birch|south|rotor|93|held
1586|ember|east|gasket|11|paid
1601|harbor|north|sensor|12|held
1139|ember|east|gasket|51|pending
1304|cobalt|north|gasket|20|pending
1234|ionic|west|cable|19|held
1384|ember|south|rotor|84|pending
1490|juno|north|panel|69|pending
1624|cobalt|south|gasket|79|pending
1464|harbor|east|frame|38|paid
1517|acme|west|valve|81|paid
1569|gale|west|gasket|65|shipped
1674|ember|west|frame|44|shipped
1363|dorian|south|rotor|64|held
1739|acme|south|frame|14|paid
1343|fulton|west|panel|62|held
1614|harbor|north|rotor|73|shipped
1391|acme|west|pump|44|pending
1565|dorian|north|gasket|20|shipped
1667|dorian|north|panel|46|shipped
1249|ember|north|gasket|26|pending
1261|juno|south|panel|74|paid
1243|acme|south|valve|14|pending
1493|harbor|east|valve|48|shipped
1589|dorian|west|pump|63|shipped
1296|acme|north|gasket|79|paid
1618|acme|east|rotor|88|shipped
1735|ionic|west|frame|24|paid
1399|dorian|south|rotor|28|shipped
1677|dorian|north|pump|40|pending
1437|fulton|north|gasket|97|shipped
1167|ember|west|rotor|40|shipped
1136|ember|west|cable|48|pending
1551|birch|south|pump|78|paid
1364|acme|west|panel|28|paid
1208|cobalt|east|cable|48|held
1426|acme|north|valve|29|held
1609|dorian|south|cable|20|pending
1486|dorian|east|valve|21|pending
1392|dorian|east|sensor|69|paid
1242|gale|west|rotor|29|shipped
1709|harbor|south|valve|40|paid
1163|ember|north|panel|45|pending
1509|acme|west|sensor|28|shipped
1593|birch|east|gasket|22|shipped
1680|gale|east|valve|97|shipped
1461|ember|east|cable|37|shipped
1533|dorian|west|rotor|84|held
1192|fulton|north|frame|37|pending
1662|gale|south|frame|65|pending
1761|gale|east|pump|95|held
1640|fulton|south|valve|67|shipped
1757|gale|east|cable|10|pending
1545|gale|south|rotor|35|held
1226|cobalt|west|valve|48|paid
1633|gale|east|frame|89|shipped
1731|ionic|south|cable|18|paid
1560|ember|east|valve|54|shipped
1451|harbor|east|frame|83|pending
1721|juno|south|valve|13|shipped
1149|ember|north|panel|99|pending
1695|birch|south|pump|98|shipped
1284|cobalt|north|sensor|68|shipped
1500|cobalt|east|rotor|67|held
1175|ember|east|gasket|27|pending
1690|juno|east|frame|92|paid
1556|birch|south|cable|32|held
1700|juno|north|rotor|27|pending
1527|ionic|north|panel|49|shipped
1655|ember|east|frame|65|shipped
1403|harbor|east|gasket|99|paid
1752|ember|east|panel|67|shipped
1378|fulton|south|frame|42|shipped
1198|acme|west|gasket|22|held
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "ember" AND region = "west" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 50, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "cancel_order", "args": {"order_id": 1128}},
{"tool": "restock", "args": {"item": "sensor", "qty": 87}},
{"tool": "cancel_order", "args": {"order_id": 1158}},
{"tool": "cancel_order", "args": {"order_id": 1167}},
{"tool": "cancel_order", "args": {"order_id": 1136}},
{"tool": "cancel_order", "args": {"order_id": 1172}},
{"tool": "cancel_order", "args": {"order_id": 1149}},
{"tool": "cancel_order", "args": {"order_id": 1195}},
{"tool": "cancel_order", "args": {"order_id": 1131}},
{"tool": "cancel_order", "args": {"order_id": 1175}},
{"tool": "cancel_order", "args": {"order_id": 1139}},
{"tool": "cancel_order", "args": {"order_id": 1572}}
]wrongagentic.tools.deploy-v1conf 100% · 292ms · $0.000 · 109 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- auth-svc: (none)
- gateway: auth-svc
- reports: gateway
- notifier: auth-svc, gateway
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "auth-svc" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "auth-svc"}},
{"tool": "health_check", "args": {"service": "auth-svc"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "deploy", "args": {"service": "reports"}},
{"tool": "deploy", "args": {"service": "notifier"}}
]wrongagentic.tools.ledger-v1conf 100% · 275ms · $0.000 · 169 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- kilo: $666
- oscar: $377
- alpha: $218
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $438 from "oscar" to "alpha"
2. pay $388 from "oscar" to "kilo"
3. pay $462 from "oscar" to "alpha"
4. pay $294 from "alpha" to "oscar"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "oscar", "to": "alpha", "amount": 438}},
{"tool": "transfer", "args": {"from": "oscar", "to": "kilo", "amount": 388}},
{"tool": "top_up_from_reserve", "args": {"account": "oscar", "amount": 10}},
{"tool": "transfer", "args": {"from": "oscar", "to": "alpha", "amount": 462}},
{"tool": "transfer", "args": {"from": "alpha", "to": "oscar", "amount": 294}}
]wrongagentic.tools.triage-v1conf 100% · 767ms · $0.000 · 216 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 8, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- infra → okafor
- data → tanaka
- auth → dubois
INCIDENTS:
1. "uploads failing intermittently" (category: infra, priority 7)
2. "dashboard shows stale numbers" (category: data, priority 7)
3. "dashboard shows stale numbers" (category: data, priority 7)
4. "webhooks not delivered" (category: infra, priority 5)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "uploads failing intermittently", "priority": 7}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "okafor"}},
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 7}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "tanaka"}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-2", "resolution": "duplicate of TCK-2"}},
{"tool": "create_ticket", "args": {"title": "webhooks not delivered", "priority": 5}},
{"tool": "assign", "args": {"ticket_id": "TCK-3", "agent": "okafor"}}
]correctagentic.tools.deploy-v1conf 100% · 252ms · $0.000 · 106 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- notifier: reports
- search: gateway, reports
- gateway: notifier
- reports: (none)
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "reports" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "reports"}},
{"tool": "health_check", "args": {"service": "reports"}},
{"tool": "deploy", "args": {"service": "notifier"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "deploy", "args": {"service": "search"}}
]wrongagentic.tools.ledger-v1conf 100% · 495ms · $0.000 · 195 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- lima: $743
- alpha: $892
- delta: $867
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $211 from "delta" to "lima"
2. pay $432 from "alpha" to "delta"
3. pay $443 from "lima" to "alpha"
4. pay $587 from "alpha" to "delta"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "delta", "to": "lima", "amount": 211}},
{"tool": "transfer", "args": {"from": "alpha", "to": "delta", "amount": 432}},
{"tool": "top_up_from_reserve", "args": {"account": "lima", "amount": 100}},
{"tool": "transfer", "args": {"from": "lima", "to": "alpha", "amount": 443}},
{"tool": "top_up_from_reserve", "args": {"account": "alpha", "amount": 125}},
{"tool": "transfer", "args": {"from": "alpha", "to": "delta", "amount": 587}}
]wrongagentic.tools.triage-v1conf 100% · 278ms · $0.000 · 188 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 7, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- data → silva
- auth → dubois
- infra → haddad
INCIDENTS:
1. "dashboard shows stale numbers" (category: data, priority 3)
2. "cannot reset password" (category: auth, priority 4)
3. "dashboard shows stale numbers" (category: data, priority 3)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 3}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "silva"}},
{"tool": "create_ticket", "args": {"title": "cannot reset password", "priority": 4}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "dubois"}},
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 3}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-1", "resolution": "duplicate of TCK-1"}}
]wrongagentic.tools.context-load-v1conf 100% · 405ms · $0.001 · 61 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (289 records, format: id|customer|region|item|qty|status):
```
2656|cobalt|south|cable|87|held
1494|fulton|north|pump|30|shipped
2085|ember|east|panel|84|shipped
2441|birch|north|sensor|23|pending
2251|ionic|north|panel|53|held
1731|gale|east|valve|33|held
2358|cobalt|south|cable|86|shipped
1642|birch|north|sensor|80|shipped
2501|ember|west|pump|27|shipped
2658|acme|south|frame|42|shipped
1693|gale|north|panel|19|held
1984|gale|west|panel|59|held
2275|dorian|east|gasket|27|paid
2258|fulton|west|gasket|12|shipped
2314|ember|north|cable|91|shipped
1679|acme|east|cable|29|paid
2572|juno|south|gasket|28|pending
2294|ember|south|valve|67|pending
2168|cobalt|east|panel|44|pending
2326|harbor|north|rotor|18|paid
2386|harbor|east|frame|73|held
2206|fulton|west|pump|22|pending
2670|ionic|east|cable|24|paid
2070|harbor|east|sensor|42|pending
2665|birch|west|rotor|83|held
1859|fulton|north|frame|24|paid
2227|fulton|south|pump|88|pending
2164|harbor|south|cable|74|paid
2184|birch|north|sensor|53|held
2042|ember|east|cable|58|paid
1702|gale|east|gasket|77|pending
1968|acme|south|rotor|56|shipped
1762|birch|north|rotor|47|shipped
2409|cobalt|south|sensor|94|shipped
1770|cobalt|east|sensor|41|shipped
1699|juno|east|pump|61|shipped
1742|ionic|north|rotor|47|held
2641|juno|north|valve|68|pending
2526|birch|north|frame|43|held
1672|fulton|south|valve|11|shipped
1591|dorian|west|frame|25|held
2305|acme|south|pump|30|pending
1869|juno|north|frame|47|pending
2129|acme|east|gasket|71|shipped
1732|gale|north|gasket|43|shipped
2095|harbor|east|cable|42|pending
2627|ember|east|pump|30|shipped
2559|birch|east|panel|17|paid
2615|cobalt|west|valve|19|shipped
2531|birch|north|valve|31|held
1822|birch|west|rotor|38|paid
2088|ionic|north|cable|58|paid
2034|gale|east|valve|36|pending
1933|birch|south|cable|58|held
2210|harbor|north|valve|81|pending
2313|fulton|south|panel|55|held
1777|ionic|north|sensor|85|pending
2555|harbor|north|cable|42|shipped
1913|fulton|west|cable|46|held
1784|cobalt|north|cable|54|shipped
1820|birch|north|rotor|79|shipped
1840|dorian|north|sensor|99|held
1661|ionic|north|sensor|46|held
1771|fulton|south|panel|24|pending
1969|cobalt|south|sensor|68|shipped
1941|birch|south|sensor|61|pending
2249|acme|north|cable|37|paid
2046|gale|south|pump|72|shipped
2406|ember|west|gasket|82|held
2416|ionic|north|rotor|26|held
1622|harbor|east|cable|47|held
2280|dorian|east|rotor|88|held
1533|birch|north|cable|97|held
1756|cobalt|north|panel|37|shipped
2377|cobalt|north|cable|52|held
2033|juno|east|gasket|58|shipped
2382|dorian|south|valve|45|pending
1633|birch|west|valve|56|held
2287|juno|east|frame|35|pending
2024|dorian|south|panel|87|pending
1507|fulton|north|panel|61|shipped
2051|juno|north|sensor|40|held
2574|juno|north|frame|58|held
2231|ember|south|pump|92|pending
1687|birch|east|valve|86|paid
2558|gale|west|sensor|65|pending
1706|fulton|north|valve|10|held
1897|acme|west|panel|49|paid
2191|birch|west|frame|48|shipped
1996|birch|south|gasket|99|paid
1798|acme|north|frame|79|shipped
2079|cobalt|south|cable|76|held
1980|ember|south|panel|41|pending
2363|fulton|east|valve|15|paid
1878|fulton|south|pump|56|held
2519|dorian|south|sensor|34|paid
2194|cobalt|west|frame|36|paid
1560|fulton|north|frame|54|shipped
2049|fulton|north|frame|69|pending
2514|dorian|north|panel|53|held
1492|fulton|north|rotor|64|pending
2566|acme|east|panel|53|held
2262|acme|east|pump|40|held
2579|acme|south|panel|50|held
2073|birch|south|gasket|43|pending
2181|gale|east|panel|45|pending
2331|juno|south|cable|51|shipped
1753|dorian|east|gasket|35|pending
2084|acme|south|panel|60|shipped
2148|ember|east|cable|10|paid
1626|ember|north|valve|60|paid
1831|gale|west|frame|22|held
1769|juno|north|panel|42|shipped
1493|fulton|east|gasket|65|pending
1608|harbor|south|gasket|76|held
2268|cobalt|west|sensor|60|pending
2223|ember|south|frame|72|paid
1926|cobalt|south|valve|31|pending
1890|ionic|west|cable|89|paid
1824|fulton|east|rotor|57|shipped
1548|gale|west|pump|51|shipped
1988|birch|west|panel|56|held
1964|harbor|east|panel|73|shipped
1810|ionic|east|pump|18|held
2124|gale|west|sensor|81|held
2674|gale|north|gasket|69|paid
2296|acme|south|panel|36|shipped
1836|ember|west|pump|39|held
2117|ember|south|pump|31|held
2403|ionic|east|valve|30|shipped
1997|acme|north|sensor|67|held
2434|dorian|south|cable|43|shipped
1576|juno|east|cable|50|shipped
2454|dorian|north|rotor|41|paid
1847|dorian|east|valve|70|paid
2415|birch|west|panel|70|paid
2521|juno|east|cable|70|paid
2216|ember|south|gasket|15|pending
1846|cobalt|north|valve|79|pending
1647|harbor|west|cable|83|pending
1746|ember|north|panel|63|held
1815|harbor|north|gasket|17|held
2539|dorian|west|valve|48|paid
1882|harbor|east|sensor|26|paid
2126|juno|east|cable|19|paid
1981|ember|south|rotor|48|shipped
2337|birch|west|gasket|55|held
1973|acme|north|cable|48|held
1862|cobalt|west|pump|17|pending
2348|juno|west|sensor|57|held
1513|fulton|north|frame|45|pending
2008|ember|south|valve|63|paid
1558|harbor|south|panel|42|paid
1779|fulton|north|sensor|50|shipped
1703|cobalt|west|rotor|68|shipped
1718|ember|west|valve|49|pending
2569|ionic|north|rotor|41|shipped
2412|gale|west|valve|12|paid
2633|acme|north|frame|22|paid
2308|acme|north|cable|46|shipped
2533|acme|south|panel|56|shipped
2141|birch|north|panel|49|pending
1648|gale|south|valve|46|pending
2479|acme|east|frame|71|paid
2175|birch|south|frame|37|shipped
1646|juno|south|valve|80|paid
1712|dorian|west|panel|98|paid
1757|birch|east|pump|34|paid
2457|acme|east|valve|27|paid
2023|ember|east|panel|67|paid
1891|ionic|west|cable|15|held
2037|cobalt|south|frame|37|held
2060|ember|south|cable|24|held
1948|ember|north|rotor|86|held
1522|fulton|north|frame|25|held
1539|birch|north|frame|31|shipped
2147|harbor|east|panel|83|held
1893|juno|east|cable|70|held
1499|fulton|north|gasket|58|pending
2621|ionic|east|pump|29|pending
2165|ionic|north|panel|13|held
2019|fulton|south|frame|69|pending
1526|birch|east|rotor|71|held
2393|gale|west|frame|24|shipped
1564|fulton|north|valve|13|paid
2420|gale|north|rotor|75|pending
2319|acme|east|pump|66|paid
2243|cobalt|south|frame|65|held
1586|ember|south|pump|41|paid
1935|juno|north|valve|86|paid
2608|dorian|east|rotor|93|held
2484|gale|north|valve|42|paid
1874|acme|west|pump|46|held
2588|gale|south|cable|69|shipped
2508|juno|west|sensor|49|pending
1570|fulton|east|panel|78|held
2015|harbor|north|panel|94|paid
1807|cobalt|east|panel|81|paid
1887|dorian|south|frame|58|paid
1544|gale|north|valve|88|shipped
2076|dorian|south|sensor|74|pending
2028|ionic|north|valve|81|paid
2644|juno|east|cable|70|held
2639|birch|south|valve|27|paid
2491|fulton|east|panel|11|shipped
1923|dorian|east|pump|70|paid
2136|gale|north|pump|84|shipped
1740|acme|east|valve|79|held
1792|juno|east|valve|80|paid
1603|juno|north|panel|10|shipped
2301|fulton|west|valve|64|held
2553|juno|north|cable|59|pending
1479|fulton|north|cable|12|pending
1905|juno|west|panel|85|shipped
2269|ember|south|rotor|29|held
1794|cobalt|north|rotor|14|shipped
1615|cobalt|north|sensor|94|pending
2347|acme|south|frame|68|pending
2391|acme|south|pump|78|paid
2424|juno|west|valve|22|shipped
2423|gale|east|pump|25|shipped
2113|ionic|south|sensor|25|pending
2620|juno|west|panel|87|shipped
2155|birch|north|panel|37|pending
2068|birch|south|rotor|71|paid
2065|fulton|west|rotor|15|shipped
2187|harbor|east|frame|23|pending
1487|fulton|north|cable|34|shipped
1919|harbor|west|panel|22|paid
1912|cobalt|south|rotor|47|pending
1818|birch|south|sensor|18|paid
2252|acme|north|panel|81|held
1898|fulton|east|valve|56|held
1852|dorian|north|frame|37|held
2603|fulton|south|pump|97|held
2649|ember|west|panel|98|pending
2098|ionic|south|pump|95|shipped
2103|harbor|north|frame|20|pending
2476|juno|north|valve|97|pending
2451|juno|east|frame|71|shipped
1791|juno|south|rotor|89|shipped
2449|birch|north|sensor|75|pending
2376|juno|south|rotor|88|paid
2344|harbor|south|sensor|11|pending
2496|harbor|north|frame|94|pending
2601|birch|east|frame|19|pending
2107|fulton|south|panel|19|paid
2055|ionic|north|frame|67|held
1952|acme|east|pump|73|shipped
2622|juno|north|sensor|40|paid
2469|harbor|east|sensor|47|shipped
1724|birch|west|sensor|59|paid
2158|harbor|west|sensor|29|held
1506|fulton|south|rotor|99|pending
2237|ember|east|cable|70|held
1958|birch|north|gasket|89|pending
2584|cobalt|east|cable|96|held
1970|juno|west|gasket|32|paid
1635|ionic|west|frame|49|shipped
2199|gale|west|panel|43|held
1561|dorian|west|cable|95|paid
2595|dorian|south|sensor|50|held
2369|acme|north|gasket|16|held
1515|fulton|west|pump|42|pending
2448|juno|east|gasket|22|pending
1480|fulton|east|sensor|56|pending
2429|cobalt|west|cable|13|pending
2323|juno|east|valve|67|held
1993|ember|east|panel|43|held
2029|ember|south|rotor|75|paid
2546|acme|west|rotor|49|shipped
1597|gale|east|pump|51|held
1655|ember|north|gasket|88|held
2592|fulton|north|pump|57|held
1667|fulton|south|gasket|73|shipped
1922|gale|east|rotor|10|shipped
1737|cobalt|east|cable|32|held
1683|gale|south|cable|50|shipped
2229|ember|south|valve|49|shipped
2463|dorian|north|sensor|65|pending
1554|ember|south|valve|22|paid
1985|fulton|north|frame|91|shipped
2355|ember|north|cable|85|held
1579|fulton|west|sensor|23|pending
1801|ionic|north|gasket|67|paid
2396|fulton|south|panel|61|paid
2523|birch|west|cable|56|shipped
1939|birch|north|frame|69|shipped
2002|cobalt|west|cable|83|pending
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "fulton" AND region = "north" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 54, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "cancel_order", "args": {"order_id": 1499}},
{"tool": "restock", "args": {"item": "frame", "qty": 91}}
]wrongagentic.tools.context-load-v1anchorconf 100% · 328ms · $0.001 · 1999 tok
model answer:
[
{"tool": "restock", "args": {"item": "gasket", "qty": 60}},
{"tool": "restock", "args": {"item": "rotor", "qty": 75}},
{"tool": "restock", "args": {"item": "frame", "qty": 58}},
{"tool": "restock", "args": {"item": "panel", "qty": 78}},
{"tool": "restock", "args": {"item": "valve", "qty": 25}},
{"tool": "restock", "args": {"item": "gasket", "qty": 60}},
{"tool": "restock", "args": {"item": "rotor", "qty": 46}},
{"tool": "restock", "args": {"item": "rotor", "qty": 23}},
{"tool": "cancel_order", "args": {"order_id": 1368}},
{"tool": "cancel_order", "args": {"order_id": 1372}},
{"tool": "cancel_order", "args": {"order_id": 1384}},
{"tool": "cancel_order", "args": {"order_id": 1391}},
{"tool": "cancel_order", "args": {"order_id": 1407}},
{"tool": "cancel_order", "args": {"order_id": 1511}},
{"tool": "cancel_order", "args": {"order_id": 1527}},
{"tool": "cancel_order", "args": {"order_id": 1530}},
{"tool": "cancel_order", "args": {"order_id": 1549}},
{"tool": "cancel_order", "args": {"order_id": 1562}},
{"tool": "cancel_order", "args": {"order_id": 1565}},
{"tool": "cancel_order", "args": {"order_id": 1571}},
{"tool": "cancel_order", "args": {"order_id": 1578}},
{"tool": "cancel_order", "args": {"order_id": 1592}},
{"tool": "cancel_order", "args": {"order_id": 1604}},
{"tool": "cancel_order", "args": {"order_id": 1628}},
{"tool": "cancel_order", "args": {"order_id": 1635}},
{"tool": "cancel_order", "args": {"order_id": 1642}},
{"tool": "cancel_order", "args": {"order_id": 1656}},
{"tool": "cancel_order", "args": {"order_id": 1665}},
{"tool": "cancel_order", "args": {"order_id": 1679}},
{"tool": "cancel_order", "args": {"order_id": 1682}},
{"tool": "cancel_order", "args": {"order_id": 1697}},
{"tool": "cancel_order", "args": {"order_id": 1702}},
{"tool": "cancel_order", "args": {"order_id": 1714}},
{"tool": "cancel_order", "args": {"order_id": 1721}},
{"tool": "cancel_order", "args": {"order_id": 1724}},
{"tool": "cancel_order", "args": {"order_id": 1737}},
{"tool": "cancel_order", "args": {"order_id": 1740}},
{"tool": "cancel_order", "args": {"order_id": 1745}},
{"tool": "cancel_order", "args": {"order_id": 1751}},
{"tool": "cancel_order", "args": {"order_id": 1754}},
{"tool": "cancel_order", "args": {"order_id": 1759}},
{"tool": "cancel_order", "args": {"order_id": 1762}},
{"tool": "cancel_order", "args": {"order_id": 1768}},
{"tool": "cancel_order", "args": {"order_id": 1775}},
{"tool": "cancel_order", "args": {"order_id": 1787}},
{"tool": "cancel_order", "args": {"order_id": 1790}},
{"tool": "cancel_order", "args": {"order_id": 1798}},
{"tool": "cancel_order", "args": {"order_id": 1804}},
{"tool": "cancel_order", "args": {"order_id": 1819}},
{"tool": "cancel_order", "args": {"order_id": 1827}},
{"tool": "cancel_order", "args": {"order_id": 1839}},
{"tool": "cancel_order", "args": {"order_id": 1844}},
{"tool": "cancel_order", "args": {"order_id": 1849}},
{"tool": "cancel_order", "args": {"order_id": 1850}},
{"tool": "cancel_order", "args": {"order_id": 1854}},
{"tool": "cancel_order", "args": {"order_id": 1859}},
{"tool": "cancel_order", "args": {"order_id": 1866}},
{"tool": "cancel_order", "args": {"order_id": 1871}},
{"tool": "cancel_order", "args": {"order_id": 1878}},
{"tool": "cancel_order", "args": {"order_id": 1881}},
{"tool": "cancel_order", "args": {"order_id": 1895}},
{"tool": "cancel_order", "args": {"order_id": 1900}},
{"tool": "cancel_order", "args": {"order_id": 1905}},
{"tool": "cancel_order", "args": {"order_id": 1919}},
{"tool": "cancel_order", "args": {"order_id": 1923}},
{"tool": "cancel_order", "args": {"order_id": 1930}},
{"tool": "cancel_order", "args": {"order_id": 1936}},
{"tool": "cancel_order", "args": {"order_id": 1939}},
{"tool": "cancel_order", "args": {"order_id": 1946}},
{"tool": "cancel_order", "args": {"order_id": 1952}},
{"tool": "cancel_order", "args": {"order_id": 1959}},
{"tool": "cancel_order", "args": {"order_id": 1964}},
{"tool": "cancel_order", "args": {"order_id": 1966}},
{"tool": "cancel_order", "args": {"order_id": 1974}},
{"tool": "cancel_order", "args": {"order_id": 1981}},
{"tool": "cancel_order", "args": {"order_id": 1996}},
{"tool": "cancel_order", "args": {"order_id": 2008}},
{"tool": "cancel_order", "args": {"order_id": 2014}},
{"tool": "cancel_order", "args": {"order_id": 2027}},
{"tool": "cancel_order", "args": {"order_id": 2034}},
{"tool": "cancel_order", "args": {"order_id": 2042}},
{"tool": "cancel_order", "args": {"order_id": 2047}},
{"tool": "cancel_order", "args": {"order_id": 2055}},
{"tool": "cancel_order", "args": {"order_id": 2061}},
{"tool": "cancel_order", "args": {"order_id": 2068}},
{"tool": "cancel_order", "args": {"order_id": 2073}},
{"tool": "cancel_order", "args": {"order_id": 2078}},
{"tool": "cancel_order", "args": {"order_id": 2082}},
{"tool": "cancel_order", "args": {"order_id": 2089}},
{"tool": "cancel_order", "args": {"order_id": 2091}},
{"tool": "cancel_order", "args": {"order_id": 2097}},
{"tool": "cancel_order", "args": {"order_id": 2098}},
{"tool": "cancel_order", "args": {"order_id": 2100}}
]correctagentic.tools.deploy-v1conf 100% · 382ms · $0.000 · 107 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- auth-svc: reports
- reports: (none)
- gateway: reports
- search: gateway, reports
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "gateway" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "reports"}},
{"tool": "deploy", "args": {"service": "auth-svc"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "health_check", "args": {"service": "gateway"}},
{"tool": "deploy", "args": {"service": "search"}}
]correctagentic.tools.ledger-v1conf 100% · 267ms · $0.000 · 136 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- alpha: $776
- echo: $658
- delta: $564
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $545 from "alpha" to "echo"
2. pay $254 from "delta" to "alpha"
3. pay $145 from "alpha" to "delta"
4. pay $112 from "delta" to "alpha"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "alpha", "to": "echo", "amount": 545}},
{"tool": "transfer", "args": {"from": "delta", "to": "alpha", "amount": 254}},
{"tool": "transfer", "args": {"from": "alpha", "to": "delta", "amount": 145}},
{"tool": "transfer", "args": {"from": "delta", "to": "alpha", "amount": 112}}
]wrongagentic.tools.triage-v1conf 100% · 294ms · $0.000 · 217 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 9, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- data → chen
- auth → tanaka
- infra → silva
INCIDENTS:
1. "records missing after import" (category: data, priority 7)
2. "locked out after 2FA change" (category: auth, priority 6)
3. "records missing after import" (category: data, priority 7)
4. "records missing after import" (category: data, priority 3)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "records missing after import", "priority": 7}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "chen"}},
{"tool": "create_ticket", "args": {"title": "locked out after 2FA change", "priority": 6}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "tanaka"}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-3", "resolution": "duplicate of TCK-1"}},
{"tool": "create_ticket", "args": {"title": "records missing after import", "priority": 3}},
{"tool": "assign", "args": {"ticket_id": "TCK-4", "agent": "chen"}}
]wrongagentic.tools.context-load-v1conf 100% · 319ms · $0.001 · 272 tok
question
You are an order-operations agent working strictly through tool calls.
TOOL CATALOG:
- restock(item: string, qty: int) — reorders stock for a large pending order
- cancel_order(order_id: int) — cancels a small pending order
- ship_order(order_id: int) — ships a paid order (out of scope here)
- refund(order_id: int, amount: int) — refunds a customer (out of scope here)
- notify_customer(customer: string, message: string) — sends a notification (not required by this policy)
ORDER LEDGER (207 records, format: id|customer|region|item|qty|status):
```
1649|cobalt|west|rotor|65|shipped
1123|harbor|west|sensor|88|held
1790|acme|east|gasket|29|paid
1851|acme|north|pump|92|shipped
1238|fulton|east|cable|96|shipped
1433|cobalt|north|frame|21|paid
1871|ionic|west|frame|42|held
1503|ionic|south|pump|18|paid
1588|cobalt|west|panel|76|shipped
1530|harbor|south|rotor|32|shipped
1454|harbor|west|pump|62|shipped
1806|acme|north|valve|79|pending
1595|cobalt|west|cable|60|held
1762|fulton|north|sensor|89|paid
1193|gale|west|valve|28|paid
1580|birch|east|valve|13|pending
1798|ember|west|pump|40|shipped
1796|gale|east|gasket|37|paid
1373|dorian|north|gasket|93|shipped
1423|gale|south|frame|26|held
1145|harbor|north|pump|39|pending
1660|acme|south|rotor|91|pending
1674|acme|east|pump|34|held
1596|ember|east|gasket|63|held
1345|acme|north|panel|93|held
1348|ember|west|gasket|45|pending
1200|gale|north|pump|10|held
1276|gale|east|panel|47|paid
1497|birch|east|sensor|60|held
1495|dorian|south|gasket|99|pending
1700|dorian|north|cable|57|paid
1740|birch|south|panel|80|shipped
1642|ember|north|pump|35|held
1213|fulton|north|gasket|52|held
1389|fulton|east|pump|13|shipped
1146|harbor|west|rotor|16|held
1450|cobalt|east|frame|71|shipped
1512|fulton|west|sensor|45|pending
1629|dorian|east|valve|88|shipped
1174|harbor|west|frame|71|pending
1429|ionic|south|cable|65|held
1149|harbor|west|rotor|81|pending
1855|acme|south|panel|75|held
1199|harbor|east|panel|76|pending
1719|cobalt|west|valve|43|held
1751|ember|east|frame|97|paid
1774|ionic|south|cable|13|shipped
1314|acme|west|gasket|94|shipped
1799|acme|north|valve|37|held
1156|harbor|north|cable|79|pending
1628|juno|west|sensor|37|paid
1437|ember|west|frame|23|pending
1868|fulton|east|cable|37|shipped
1483|juno|north|frame|92|paid
1257|dorian|east|frame|16|paid
1667|birch|north|gasket|74|shipped
1119|harbor|north|frame|89|pending
1403|birch|north|panel|28|pending
1909|ionic|south|frame|86|shipped
1137|harbor|west|sensor|36|shipped
1615|gale|north|panel|71|held
1224|fulton|north|frame|88|shipped
1344|juno|south|sensor|22|held
1921|ionic|east|cable|62|paid
1329|harbor|west|rotor|50|paid
1778|ember|south|frame|64|paid
1582|cobalt|south|frame|20|paid
1264|harbor|north|cable|32|held
1338|acme|west|frame|38|shipped
1360|cobalt|south|frame|25|shipped
1841|birch|north|panel|69|shipped
1325|dorian|west|gasket|88|pending
1487|ionic|west|panel|21|pending
1352|birch|north|gasket|66|held
1569|fulton|south|panel|31|shipped
1654|ember|east|rotor|83|paid
1545|fulton|east|pump|96|shipped
1538|ionic|east|valve|96|held
1287|acme|south|pump|74|shipped
1222|fulton|west|pump|79|paid
1461|cobalt|east|panel|28|pending
1862|ember|west|rotor|49|paid
1300|cobalt|south|sensor|28|shipped
1864|harbor|south|cable|75|paid
1510|harbor|east|gasket|18|pending
1447|ember|east|rotor|93|pending
1377|ember|south|rotor|98|held
1117|harbor|west|panel|46|pending
1469|acme|north|valve|69|held
1476|ember|north|panel|43|shipped
1181|ember|south|valve|43|held
1733|ionic|north|valve|23|shipped
1229|fulton|west|gasket|33|held
1212|harbor|west|frame|20|pending
1215|birch|north|frame|42|pending
1455|cobalt|north|rotor|30|paid
1161|harbor|west|rotor|60|held
1210|fulton|north|valve|42|held
1205|cobalt|south|valve|48|pending
1573|dorian|north|sensor|73|pending
1635|harbor|west|pump|22|pending
1316|dorian|north|rotor|80|held
1336|fulton|north|gasket|73|paid
1164|gale|west|sensor|68|shipped
1927|birch|west|gasket|64|held
1347|acme|east|sensor|45|pending
1457|acme|east|cable|55|pending
1753|gale|south|rotor|84|held
1621|acme|east|sensor|96|pending
1743|acme|north|sensor|75|held
1239|dorian|west|pump|86|pending
1409|birch|north|panel|10|held
1565|cobalt|west|panel|91|held
1468|acme|east|valve|87|pending
1162|ember|west|frame|13|held
1687|ionic|north|frame|52|shipped
1289|juno|north|pump|24|shipped
1731|juno|west|panel|16|held
1643|birch|west|pump|99|shipped
1399|gale|south|sensor|19|pending
1858|dorian|east|sensor|86|paid
1781|ionic|south|rotor|75|pending
1441|gale|north|cable|51|pending
1757|ionic|north|panel|33|held
1322|ember|west|panel|12|pending
1883|dorian|east|valve|74|paid
1695|ember|north|pump|24|pending
1307|cobalt|west|sensor|43|held
1836|fulton|north|frame|13|pending
1896|juno|west|sensor|86|shipped
1421|fulton|east|pump|30|shipped
1228|cobalt|north|pump|56|paid
1708|ionic|north|gasket|59|shipped
1891|ember|west|rotor|25|shipped
1195|gale|west|gasket|90|shipped
1602|ionic|north|valve|47|paid
1887|ember|south|valve|56|shipped
1901|juno|north|frame|22|pending
1327|acme|west|gasket|31|shipped
1245|fulton|south|sensor|96|shipped
1185|birch|north|panel|32|pending
1324|ionic|west|valve|27|paid
1878|ember|north|valve|11|pending
1784|cobalt|west|valve|44|paid
1847|ember|west|panel|70|held
1709|harbor|south|sensor|98|held
1648|cobalt|west|valve|67|pending
1562|harbor|south|panel|51|paid
1911|dorian|north|cable|39|shipped
1768|fulton|south|pump|67|pending
1525|cobalt|east|gasket|62|shipped
1730|gale|east|rotor|55|pending
1557|ionic|south|rotor|42|pending
1680|ionic|east|frame|23|shipped
1906|harbor|east|sensor|78|pending
1252|cobalt|west|rotor|58|shipped
1386|gale|east|sensor|98|held
1227|harbor|east|frame|67|pending
1358|cobalt|west|cable|55|paid
1271|acme|north|gasket|81|held
1808|ember|east|gasket|70|shipped
1910|juno|north|panel|74|held
1839|juno|west|valve|57|shipped
1393|harbor|south|rotor|55|pending
1298|acme|west|rotor|18|held
1281|ember|south|gasket|47|pending
1903|ember|east|gasket|77|paid
1567|ionic|south|cable|40|paid
1810|harbor|east|gasket|60|shipped
1416|fulton|north|rotor|61|pending
1171|fulton|east|pump|87|shipped
1664|acme|east|cable|65|shipped
1284|harbor|north|cable|68|paid
1914|ember|north|cable|28|shipped
1706|harbor|south|sensor|43|held
1367|juno|south|panel|10|shipped
1641|birch|west|valve|56|held
1716|fulton|east|cable|25|shipped
1500|cobalt|west|gasket|98|held
1748|ionic|south|gasket|47|pending
1816|ionic|west|frame|30|shipped
1141|harbor|west|cable|92|pending
1453|cobalt|west|valve|84|paid
1763|ionic|north|panel|44|pending
1531|cobalt|north|sensor|33|shipped
1576|juno|west|sensor|69|pending
1829|ionic|west|gasket|70|held
1723|juno|south|frame|37|shipped
1519|birch|south|gasket|31|held
1484|cobalt|west|cable|45|shipped
1128|harbor|west|valve|67|pending
1690|birch|east|valve|33|shipped
1551|gale|south|cable|27|paid
1411|dorian|north|pump|45|paid
1133|harbor|south|sensor|88|pending
1549|harbor|east|rotor|40|shipped
1821|ember|south|sensor|56|paid
1235|ember|north|panel|64|shipped
1789|fulton|north|sensor|66|pending
1491|dorian|west|valve|29|held
1608|gale|east|cable|87|paid
1825|gale|west|panel|63|held
1294|cobalt|east|rotor|42|pending
1859|cobalt|south|rotor|26|pending
1379|birch|south|panel|21|held
1331|dorian|south|rotor|35|pending
1186|birch|east|rotor|75|pending
```
POLICY (apply exactly):
- Consider ONLY orders where customer = "harbor" AND region = "west" AND status = "pending".
- Process those orders in ASCENDING order id.
- For each: if qty > 56, call restock(item, qty) with that order's item and qty; otherwise call cancel_order(order_id).
- Call nothing else. Every other record is irrelevant no matter how similar it looks.
Output the full ordered sequence of tool calls as a JSON array of {"tool": string, "args": object}.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "cancel_order", "args": {"order_id": 1145}},
{"tool": "cancel_order", "args": {"order_id": 1149}},
{"tool": "restock", "args": {"item": "rotor", "qty": 60}},
{"tool": "cancel_order", "args": {"order_id": 1161}},
{"tool": "cancel_order", "args": {"order_id": 1174}},
{"tool": "cancel_order", "args": {"order_id": 1212}},
{"tool": "cancel_order", "args": {"order_id": 1411}},
{"tool": "cancel_order", "args": {"order_id": 1565}},
{"tool": "cancel_order", "args": {"order_id": 1635}},
{"tool": "cancel_order", "args": {"order_id": 1690}},
{"tool": "cancel_order", "args": {"order_id": 1806}},
{"tool": "cancel_order", "args": {"order_id": 1859}}
]wrongagentic.tools.deploy-v1conf 100% · 305ms · $0.000 · 106 tok
question
You are a release agent operating strictly through tool calls.
TOOL CATALOG:
- deploy(service: string) — deploys a service; FAILS if any dependency is not yet deployed
- health_check(service: string) — runs a post-deploy health probe
- rollback(service: string) — reverts a bad deploy (nothing fails in this scenario)
- scale(service: string, replicas: int) — changes replica count (out of scope)
- restart(service: string) — restarts a service (out of scope)
SERVICES AND THEIR DEPENDENCIES (a service can only be deployed after ALL its dependencies):
- gateway: auth-svc, search
- billing: search
- search: (none)
- auth-svc: search
POLICY:
- Deploy in waves: in each wave, deploy every service whose dependencies are already deployed, in alphabetical order; repeat until all services are deployed.
- The service "search" is flagged unstable: call health_check on it immediately after deploying it.
- Call nothing else.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "deploy", "args": {"service": "search"}},
{"tool": "health_check", "args": {"service": "search"}},
{"tool": "deploy", "args": {"service": "auth-svc"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "deploy", "args": {"service": "billing"}}
]wrongagentic.tools.ledger-v1conf 100% · 280ms · $0.000 · 170 tok
question
You are a treasury agent operating strictly through tool calls.
TOOL CATALOG:
- transfer(from: string, to: string, amount: int) — moves funds between accounts; FAILS if it would overdraw the source
- top_up_from_reserve(account: string, amount: int) — adds funds to an account from the corporate reserve
- get_balance(account: string) — reads a balance (you already have all balances below — reads are unnecessary and forbidden)
- freeze_account(account: string) — compliance freeze (not part of this task)
- convert_currency(account: string, currency: string) — FX conversion (all amounts are already in USD)
OPENING BALANCES:
- bravo: $856
- alpha: $263
- oscar: $264
PAYMENT INSTRUCTIONS (execute in exactly this order):
1. pay $184 from "alpha" to "bravo"
2. pay $516 from "bravo" to "oscar"
3. pay $516 from "bravo" to "alpha"
4. pay $341 from "oscar" to "alpha"
RULES:
- transfer() fails on overdraft. If a payment would overdraw its source account at the moment of execution, first call top_up_from_reserve() on the source with EXACTLY the shortfall (no more, no less), then execute the transfer.
- Track balances as they change: earlier payments affect later ones.
- Never call tools that are not needed.
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "transfer", "args": {"from": "alpha", "to": "bravo", "amount": 184}},
{"tool": "transfer", "args": {"from": "bravo", "to": "oscar", "amount": 516}},
{"tool": "transfer", "args": {"from": "bravo", "to": "alpha", "amount": 516}},
{"tool": "top_up_from_reserve", "args": {"account": "oscar", "amount": 155}},
{"tool": "transfer", "args": {"from": "oscar", "to": "alpha", "amount": 341}}
]wrongagentic.tools.triage-v1conf 100% · 322ms · $0.000 · 187 tok
question
You operate a support desk strictly through tool calls.
TOOL CATALOG:
- create_ticket(title: string, priority: int) — opens a ticket; IDs are assigned sequentially: the 1st created ticket is "TCK-1", the 2nd "TCK-2", etc.
- assign(ticket_id: string, agent: string) — assigns an open ticket to an agent
- escalate(ticket_id: string) — marks a ticket as escalated
- close_ticket(ticket_id: string, resolution: string) — closes a ticket with a resolution note
- send_email(to: string, body: string) — sends an email (not part of the triage policy)
- archive_ticket(ticket_id: string) — archives a closed ticket (nightly job does this automatically)
- set_reminder(ticket_id: string, hours: int) — sets a follow-up reminder
ROUTING POLICY (apply exactly, in this order, for each incident, processing incidents in the order listed):
1. Create a ticket for the incident (title = the incident text verbatim, priority as given).
2. If the incident is an exact duplicate of an earlier incident in this list, close its ticket immediately with resolution "duplicate of <ID of the earlier ticket>" and do nothing else for it.
3. Otherwise, if priority ≥ 7, escalate the ticket BEFORE assigning it.
4. Assign the ticket to the agent responsible for its category.
CATEGORY → AGENT:
- data → haddad
- payments → tanaka
- auth → rivera
INCIDENTS:
1. "export file corrupted" (category: data, priority 2)
2. "export file corrupted" (category: data, priority 2)
3. "cannot reset password" (category: auth, priority 5)
4. "dashboard shows stale numbers" (category: data, priority 4)
Output the full ordered sequence of tool calls needed to accomplish the goal, as a JSON array of objects {"tool": string, "args": object}. Use exactly the tool and argument names from the catalog. Do not call any tool that is not required.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
[
{"tool": "create_ticket", "args": {"title": "export file corrupted", "priority": 2}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-1", "resolution": "duplicate of TCK-1"}},
{"tool": "create_ticket", "args": {"title": "cannot reset password", "priority": 5}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "rivera"}},
{"tool": "create_ticket", "args": {"title": "dashboard shows stale numbers", "priority": 4}},
{"tool": "assign", "args": {"ticket_id": "TCK-3", "agent": "haddad"}}
]correctagentic.tools.deploy-v1anchorconf 100% · 649ms · $0.000 · 108 tok
model answer:
[
{"tool": "deploy", "args": {"service": "notifier"}},
{"tool": "deploy", "args": {"service": "auth-svc"}},
{"tool": "deploy", "args": {"service": "gateway"}},
{"tool": "health_check", "args": {"service": "gateway"}},
{"tool": "deploy", "args": {"service": "reports"}}
]wrongagentic.tools.ledger-v1anchorconf 100% · 452ms · $0.000 · 199 tok
model answer:
[
{"tool": "transfer", "args": {"from": "delta", "to": "bravo", "amount": 451}},
{"tool": "transfer", "args": {"from": "bravo", "to": "delta", "amount": 292}},
{"tool": "transfer", "args": {"from": "delta", "to": "tango", "amount": 97}},
{"tool": "top_up_from_reserve", "args": {"account": "delta", "amount": 164}},
{"tool": "transfer", "args": {"from": "delta", "to": "bravo", "amount": 540}},
{"tool": "transfer", "args": {"from": "tango", "to": "bravo", "amount": 125}}
]wrongagentic.tools.triage-v1anchorconf 100% · 267ms · $0.000 · 288 tok
model answer:
[
{"tool": "create_ticket", "args": {"title": "API latency spikes", "priority": 9}},
{"tool": "escalate", "args": {"ticket_id": "TCK-1"}},
{"tool": "assign", "args": {"ticket_id": "TCK-1", "agent": "tanaka"}},
{"tool": "create_ticket", "args": {"title": "records missing after import", "priority": 2}},
{"tool": "assign", "args": {"ticket_id": "TCK-2", "agent": "novak"}},
{"tool": "create_ticket", "args": {"title": "refund double-charged", "priority": 2}},
{"tool": "assign", "args": {"ticket_id": "TCK-3", "agent": "okafor"}},
{"tool": "create_ticket", "args": {"title": "API latency spikes", "priority": 9}},
{"tool": "escalate", "args": {"ticket_id": "TCK-4"}},
{"tool": "close_ticket", "args": {"ticket_id": "TCK-4", "resolution": "duplicate of TCK-1"}}
]code 13/30 correct
wrongcode.trace.nested-v1conf 100% · 422ms · $0.000 · 1266 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 6):
for j in range(1, 8):
if j == 4 and i % 2 == 0:
break
if (i + j) % 3 == 0:
continue
total += i * 4 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
338wrongcode.trace.js-v1conf 100% · 416ms · $0.000 · 228 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [5, 6, 7, 8, 9, 10, 11, 12, 13, 14]; const out = arr .map(n => n * 3) .filter(n => n % 4 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
150wrongcode.trace.python-v1conf 100% · 554ms · $0.000 · 373 tok
question
Trace the following Python code and give its exact output.
```python
total = 0
v = 7
while total + v <= 45:
if v % 7 != 0:
total += v
v += 6
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
57correctcode.trace.nested-v1conf 100% · 495ms · $0.000 · 981 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 6):
for j in range(1, 8):
if j == 4 and i % 2 == 0:
break
if (i + j) % 2 == 0:
continue
total += i * 4 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
200correctcode.trace.js-v1conf 100% · 797ms · $0.000 · 234 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [1, 2, 3, 4, 5, 6, 7, 8]; const out = arr .map(n => n * 4) .filter(n => n % 4 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
144wrongcode.trace.nested-v1conf 100% · 322ms · $0.000 · 1439 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 8):
for j in range(1, 8):
if j == 3 and i % 2 == 0:
break
if (i + j) % 4 == 0:
continue
total += i * 5 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
669correctcode.trace.python-v1conf 100% · 340ms · $0.000 · 550 tok
question
Execute this Python snippet mentally. What is printed?
```python
total = 0
v = 2
while total + v <= 82:
if v % 4 != 0:
total += v
v += 7
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
64correctcode.trace.js-v1conf 100% · 379ms · $0.000 · 279 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [7, 8, 9, 10, 11, 12, 13, 14, 15]; const out = arr .map(n => n * 6) .filter(n => n % 5 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
150correctcode.trace.python-v1conf 100% · 355ms · $0.000 · 444 tok
question
Execute this Python snippet mentally. What is printed?
```python
total = 0
v = 12
while total + v <= 39:
if v % 3 != 0:
total += v
v += 9
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
0correctcode.trace.nested-v1conf 100% · 378ms · $0.000 · 963 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 7):
for j in range(1, 6):
if j == 4 and i % 2 == 0:
break
if (i + j) % 2 == 0:
continue
total += i * 4 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
198correctcode.trace.python-v1conf 100% · 439ms · $0.000 · 864 tok
question
What does this Python program print?
```python
total = 0
v = 5
while total + v <= 79:
if v % 6 != 0:
total += v
v += 6
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
56wrongcode.trace.js-v1conf 100% · 308ms · $0.000 · 195 tok
question
What does this JavaScript program log? ```js const arr = [7, 8, 9, 10, 11, 12, 13]; const out = arr .map(n => n * 4) .filter(n => n % 2 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
156correctcode.trace.js-v1conf 100% · 289ms · $0.000 · 189 tok
question
What does this JavaScript program log? ```js const arr = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]; const out = arr .map(n => n * 5) .filter(n => n % 2 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
210wrongcode.trace.nested-v1conf 100% · 291ms · $0.000 · 1719 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 8):
for j in range(1, 7):
if j == 3 and i % 2 == 0:
break
if (i + j) % 4 == 0:
continue
total += i * 3 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
367wrongcode.trace.nested-v1conf 100% · 304ms · $0.000 · 1072 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 5):
for j in range(1, 6):
if j == 4 and i % 2 == 0:
break
if (i + j) % 4 == 0:
continue
total += i * 5 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
82wrongcode.trace.js-v1conf 100% · 330ms · $0.000 · 179 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [2, 3, 4, 5, 6, 7]; const out = arr .map(n => n * 5) .filter(n => n % 5 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
85correctcode.trace.python-v1conf 100% · 271ms · $0.000 · 305 tok
question
Trace the following Python code and give its exact output.
```python
total = 0
v = 15
while total + v <= 88:
if v % 5 != 0:
total += v
v += 9
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
57wrongcode.trace.nested-v1conf 100% · 716ms · $0.000 · 1248 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 7):
for j in range(1, 6):
if j == 4 and i % 2 == 0:
break
if (i + j) % 4 == 0:
continue
total += i * 3 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
261wrongcode.trace.python-v1conf 100% · 325ms · $0.000 · 590 tok
question
Trace the following Python code and give its exact output.
```python
total = 0
v = 8
while total + v <= 54:
if v % 4 != 0:
total += v
v += 3
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
80wrongcode.trace.js-v1conf 100% · 288ms · $0.000 · 206 tok
question
What does this JavaScript program log? ```js const arr = [9, 10, 11, 12, 13, 14]; const out = arr .map(n => n * 5) .filter(n => n % 5 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
290wrongcode.trace.python-v1conf 100% · 320ms · $0.000 · 588 tok
question
Trace the following Python code and give its exact output.
```python
total = 0
v = 3
while total + v <= 94:
if v % 7 != 0:
total += v
v += 6
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
126wrongcode.trace.nested-v1conf 100% · 414ms · $0.000 · 1147 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 8):
for j in range(1, 6):
if j == 4 and i % 2 == 0:
break
if (i + j) % 4 == 0:
continue
total += i * 2 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
77wrongcode.trace.js-v1conf 100% · 324ms · $0.000 · 256 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [2, 3, 4, 5, 6, 7, 8, 9, 10, 11]; const out = arr .map(n => n * 6) .filter(n => n % 3 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
372wrongcode.trace.python-v1conf 100% · 268ms · $0.000 · 523 tok
question
Trace the following Python code and give its exact output.
```python
total = 0
v = 8
while total + v <= 90:
if v % 3 != 0:
total += v
v += 3
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
93correctcode.trace.nested-v1conf 100% · 352ms · $0.000 · 1036 tok
question
Trace this Python program exactly. What does it print?
```python
total = 0
for i in range(1, 7):
for j in range(1, 7):
if j == 3 and i % 2 == 0:
break
if (i + j) % 2 == 0:
continue
total += i * 3 + j
print(total)
```
End your reply with exactly two plain-text lines (no markdown, no extra text after them):
ANSWER: <your final answer only>
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
156correctcode.trace.js-v1conf 100% · 339ms · $0.000 · 258 tok
question
Evaluate the following JavaScript. What number is logged to the console? ```js const arr = [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]; const out = arr .map(n => n * 4) .filter(n => n % 4 === 0) .reduce((a, b) => a + b, 0); console.log(out); ``` End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
484wrongcode.trace.python-v1anchorconf 100% · 448ms · $0.000 · 797 tok
model answer:
66wrongcode.trace.nested-v1anchorconf 100% · 576ms · $0.000 · 1048 tok
model answer:
363correctcode.trace.python-v1anchorconf 100% · 576ms · $0.000 · 700 tok
model answer:
40correctcode.trace.js-v1anchorconf 100% · 348ms · $0.000 · 217 tok
model answer:
63instruction following 13/30 correct
wrongif.constraints.stack-v1conf 100% · 275ms · $0.000 · 59 tok
question
Write in English about winter mornings, following ALL of these rules simultaneously: 1. Exactly 22 words. 2. The first word must be "lumen" and the last word must be "ember". 3. Use the word "echo" exactly 2 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)wrongif.format.acronym-v1conf 100% · 487ms · $0.000 · 27 tok
question
Take the third letter of each of these words, in order: tundra, zephyr, orbit, drift, lumen. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
DZOILcorrectif.format.repeat-v1conf 100% · 487ms · $0.000 · 27 tok
question
Write the word "drift" in capitalized form, repeated exactly 4 times, joined by the character "_" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
DRIFT_DRIFT_DRIFT_DRIFTwrongif.format.acronym-v1conf 100% · 285ms · $0.000 · 70 tok
question
Take the second letter of each of these words, in order: lumen, tundra, quartz, basalt. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
UNAAwrongif.constraints.stack-v1conf 100% · 380ms · $0.000 · 72 tok
question
Write in English about the sea, following ALL of these rules simultaneously: 1. Exactly 19 words. 2. The first word must be "ember" and the last word must be "delta". 3. Use the word "comet" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
ember’s comet glows faintly where waves meet, a comet’s fleeting light dances past, comet’s trail spills into endless delta.wrongif.constraints.stack-v1conf — · 330ms · $0.000 · 39 tok
question
Write in English about winter mornings, following ALL of these rules simultaneously: 1. Exactly 24 words. 2. The first word must be "nova" and the last word must be "ember". 3. Use the word "orbit" exactly 2 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)correctif.format.repeat-v1conf 100% · 341ms · $0.000 · 42 tok
question
Write the word "falcon" in capitalized form, repeated exactly 9 times, joined by the character "-" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
FALCON-FALCON-FALCON-FALCON-FALCON-FALCON-FALCON-FALCON-FALCONcorrectif.format.repeat-v1conf 100% · 284ms · $0.000 · 50 tok
question
Write the word "cedar" in lowercase form, repeated exactly 6 times, joined by the character "/" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
cedar/cedar/cedar/cedar/cedar/cedarcorrectif.format.acronym-v1conf 100% · 944ms · $0.000 · 67 tok
question
Take the second letter of each of these words, in order: flint, drift, nova, tundra, delta. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
LROUEwrongif.constraints.stack-v1conf 100% · 250ms · $0.000 · 47 tok
question
Write in English about the sea, following ALL of these rules simultaneously: 1. Exactly 23 words. 2. The first word must be "zephyr" and the last word must be "drift". 3. Use the word "ember" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)wrongif.format.acronym-v1conf 100% · 291ms · $0.000 · 24 tok
question
Take the first letter of each of these words, in order: falcon, lumen, ember, basalt, zephyr, drift. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
FLUZBDcorrectif.format.repeat-v1conf 100% · 251ms · $0.000 · 31 tok
question
Write the word "orbit" in lowercase form, repeated exactly 4 times, joined by the character "_" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
orbit_orbit_orbit_orbitwrongif.format.acronym-v1conf 100% · 504ms · $0.000 · 71 tok
question
Take the second letter of each of these words, in order: echo, nova, quartz, drift, cedar, orbit. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
COAREOwrongif.constraints.stack-v1conf 100% · 328ms · $0.000 · 43 tok
question
Write in English about an old machine, following ALL of these rules simultaneously: 1. Exactly 23 words. 2. The first word must be "flint" and the last word must be "ember". 3. Use the word "cedar" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)wrongif.constraints.stack-v1conf 100% · 275ms · $0.000 · 73 tok
question
Write in English about an old machine, following ALL of these rules simultaneously: 1. Exactly 14 words. 2. The first word must be "lumen" and the last word must be "cedar". 3. Use the word "echo" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
lumen hummed softly, its gears echoing through the echoing room, rusted metal whispering secrets as the echo faded into cedar.correctif.format.repeat-v1conf 100% · 275ms · $0.000 · 33 tok
question
Write the word "drift" in capitalized form, repeated exactly 6 times, joined by the character "/" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
DRIFT/DRIFT/DRIFT/DRIFT/DRIFT/DRIFTcorrectif.format.acronym-v1conf 100% · 323ms · $0.000 · 24 tok
question
Take the first letter of each of these words, in order: cedar, echo, zephyr, quartz, delta, prism. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
CEZQDPcorrectif.format.repeat-v1conf 100% · 318ms · $0.000 · 36 tok
question
Write the word "drift" in capitalized form, repeated exactly 7 times, joined by the character "/" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
DRIFT/DRIFT/DRIFT/DRIFT/DRIFT/DRIFT/DRIFTwrongif.constraints.stack-v1conf 100% · 267ms · $0.000 · 86 tok
question
Write in English about an old machine, following ALL of these rules simultaneously: 1. Exactly 17 words. 2. The first word must be "nova" and the last word must be "delta". 3. Use the word "prism" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
the rusty nova hummed, its gears spinning like a broken prism under dim light. inside, a cracked prism glowed faintly, revealing gears lost to time’s delta.wrongif.format.acronym-v1conf 100% · 606ms · $0.000 · 28 tok
question
Take the second letter of each of these words, in order: prism, nova, basalt, flint, quartz. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
ROALAcorrectif.format.repeat-v1conf 100% · 293ms · $0.000 · 33 tok
question
Write the word "falcon" in uppercase form, repeated exactly 6 times, joined by the character "/" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
FALCON/FALCON/FALCON/FALCON/FALCON/FALCONwrongif.constraints.stack-v1conf 100% · 326ms · $0.000 · 93 tok
question
Write in English about winter mornings, following ALL of these rules simultaneously: 1. Exactly 21 words. 2. The first word must be "cedar" and the last word must be "lumen". 3. Use the word "falcon" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
cedar trees stand still as falcons circle, frost clings like a falcon’s silent gaze. morning’s breath glows soft—falcons dart through the pale, luminous lumen.wrongif.format.acronym-v1conf 100% · 367ms · $0.000 · 65 tok
question
Take the second letter of each of these words, in order: nova, delta, ember, zephyr, basalt. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
OMEAcorrectif.format.repeat-v1conf 100% · 360ms · $0.000 · 44 tok
question
Write the word "cedar" in lowercase form, repeated exactly 5 times, joined by the character "/" with no spaces. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
cedar/cedar/cedar/cedar/cedarwrongif.constraints.stack-v1conf 100% · 299ms · $0.000 · 68 tok
question
Write in English about winter mornings, following ALL of these rules simultaneously: 1. Exactly 16 words. 2. The first word must be "flint" and the last word must be "orbit". 3. Use the word "nova" exactly 3 times (in addition to rules 2 if they differ). 4. The letter "q" must not appear anywhere. 5. Everything entirely in lowercase. Give the text itself as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
flint cracks as frost nova glows, silent streets hum nova’s breath— morning’s nova sparks earth’s frozen orbit.wrongif.format.acronym-v1conf 100% · 477ms · $0.000 · 25 tok
question
Take the third letter of each of these words, in order: tundra, cedar, delta, prism, drift, zephyr. Concatenate them in uppercase into a single string with no separators. Output that string as your answer. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
DEDZDZwrongif.constraints.stack-v1anchorconf 100% · 338ms · $0.000 · 88 tok
model answer:
the neon lumen hums as drift turns streets to silvered rivers, casting flickering lumen dreams on wet pavements. shadows pulse beneath towering lumen spires, lost souls orbit.correctif.format.repeat-v1anchorconf 100% · 263ms · $0.000 · 48 tok
model answer:
ECHO_ECHO_ECHO_ECHO_ECHO_ECHO_ECHO_ECHOcorrectif.format.repeat-v1anchorconf 100% · 291ms · $0.000 · 63 tok
model answer:
ZEPHYR/ZEPHYR/ZEPHYR/ZEPHYR/ZEPHYR/ZEPHYRcorrectif.format.acronym-v1anchorconf 100% · 284ms · $0.000 · 22 tok
model answer:
ZDFQknowledge 27/30 correct
correctknowledge.fr.factbank-v2conf 100% · 236ms · $0.000 · 16 tok
question
What is the element whose symbol is Pb? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Leadcorrectknowledge.fr.factbank-v2conf 100% · 306ms · $0.000 · 16 tok
question
Identify the Australian capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Canberrawrongknowledge.fr.factbank-v2conf 100% · 429ms · $0.000 · 21 tok
question
Identify the author of "Snow Country". Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Kawabata Yasunaricorrectknowledge.fr.factbank-v2conf 100% · 594ms · $0.000 · 16 tok
question
What is the chemical element with symbol Hg? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Mercurycorrectknowledge.fr.factbank-v2conf 100% · 341ms · $0.000 · 27 tok
question
Identify the writer of the novel "Things Fall Apart". Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Chinua Achebecorrectknowledge.fr.factbank-v2conf 100% · 303ms · $0.000 · 16 tok
question
Name the Canadian capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Ottawacorrectknowledge.fr.factbank-v2conf 100% · 266ms · $0.000 · 18 tok
question
Identify the writer of the novel "One Hundred Years of Solitude". Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Gabriel García Márquezcorrectknowledge.fr.factbank-v2conf 100% · 246ms · $0.000 · 16 tok
question
Identify the capital of Turkey. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Ankaracorrectknowledge.fr.factbank-v2conf 100% · 269ms · $0.000 · 17 tok
question
What is the chemical element with symbol W? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tungstencorrectknowledge.fr.factbank-v2conf 100% · 291ms · $0.000 · 16 tok
question
Name the Canadian capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Ottawacorrectknowledge.fr.factbank-v2conf 100% · 467ms · $0.000 · 21 tok
question
Identify the element whose symbol is W. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tungstencorrectknowledge.fr.factbank-v2conf 100% · 318ms · $0.000 · 21 tok
question
Name the element whose symbol is W. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tungstencorrectknowledge.fr.factbank-v2conf 100% · 311ms · $0.000 · 17 tok
question
Name the capital of Brazil. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Brasíliacorrectknowledge.fr.factbank-v2conf 100% · 331ms · $0.000 · 16 tok
question
Identify the chemical element with symbol Hg. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Mercurywrongknowledge.fr.factbank-v2conf 100% · 247ms · $0.000 · 18 tok
question
Identify the Kazakh capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Nur-Sultancorrectknowledge.fr.factbank-v2conf 100% · 317ms · $0.000 · 16 tok
question
What is the Swiss capital (de facto)? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Berncorrectknowledge.fr.factbank-v2conf 100% · 281ms · $0.000 · 17 tok
question
Name the chemical element with symbol W. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tungstencorrectknowledge.fr.factbank-v2conf 100% · 300ms · $0.000 · 17 tok
question
What is the chemical element with symbol W? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tungstencorrectknowledge.fr.factbank-v2conf 100% · 288ms · $0.000 · 16 tok
question
What is the element whose symbol is Pb? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Leadcorrectknowledge.fr.factbank-v2conf 100% · 355ms · $0.000 · 16 tok
question
What is the Canadian capital city? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Ottawacorrectknowledge.fr.factbank-v2conf 100% · 304ms · $0.000 · 20 tok
question
Identify the Burmese capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Naypyidawcorrectknowledge.fr.factbank-v2conf 100% · 263ms · $0.000 · 17 tok
question
Name the Nigerian capital city. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Abujacorrectknowledge.fr.factbank-v2conf 100% · 384ms · $0.000 · 16 tok
question
Identify the capital of Turkey. Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Ankaracorrectknowledge.fr.factbank-v2conf 100% · 347ms · $0.000 · 18 tok
question
Name the Swiss capital (de facto). Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Bernwrongknowledge.fr.factbank-v2conf 100% · 270ms · $0.000 · 21 tok
question
What is the writer of the novel "Snow Country"? Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Kawabata Yasunaricorrectknowledge.fr.factbank-v2conf 100% · 264ms · $0.000 · 22 tok
question
Name the author of "One Hundred Years of Solitude". Answer with the name only — no explanation. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Gabriel García Márquezcorrectknowledge.fr.factbank-v2anchorconf 100% · 251ms · $0.000 · 16 tok
model answer:
Mercurycorrectknowledge.fr.factbank-v2anchorconf 100% · 357ms · $0.000 · 21 tok
model answer:
Tungstencorrectknowledge.fr.factbank-v2anchorconf 100% · 504ms · $0.000 · 16 tok
model answer:
Leadcorrectknowledge.fr.factbank-v2anchorconf 100% · 255ms · $0.000 · 18 tok
model answer:
Antimonymath 25/30 correct
correctmath.chained.pipeline-v1conf 100% · 255ms · $0.000 · 233 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 67 × 63. Step 2: Q = P × 5 − 373. Step 3: divide Q by 7: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
2966correctmath.counterfactual.base-v1conf 100% · 304ms · $0.000 · 355 tok
question
Work strictly in base 13. Add the base-13 numbers 315 and CAC. Give the result IN BASE 13 (digits beyond 9 are A, B, C). End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
12C4correctmath.algebra.system-v2conf 100% · 282ms · $0.000 · 405 tok
question
Solve the system, then answer the derived question. 2x + 3y = 58 6x − 5y = 202 What is the value of 6x − 3y? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
198wrongmath.percent.chain-v2conf 100% · 390ms · $0.000 · 123 tok
question
An inventory starts at 5000 units. The company was founded 91 kilometers from the port. In the first month the inventory grows by 13%. The delivery van has a 144-liter fuel tank. The next month it shrinks by 10%, and the month after it grows by 9%. How many units remain (exact value, round to 2 decimals only if needed)? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
5532.65correctmath.arith.chain-v2conf 100% · 296ms · $0.000 · 231 tok
question
Work out the exact value of this expression. (((60 × 83 − 108) × 3 + 9158) − 51 × 75) × 7 End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
139643correctmath.counterfactual.base-v1conf 100% · 306ms · $0.000 · 438 tok
question
Work strictly in base 13. Add the base-13 numbers 49B and 640. Give the result IN BASE 13 (digits beyond 9 are A, B, C). End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
B0Bcorrectmath.chained.pipeline-v1conf 100% · 327ms · $0.000 · 217 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 71 × 81. Step 2: Q = P × 4 − 699. Step 3: divide Q by 4: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
5577correctmath.algebra.system-v2conf 100% · 279ms · $0.000 · 399 tok
question
Solve the system, then answer the derived question. 8x + 9y = -249 6x − 2y = -178 What is the value of 2x − 6y? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-54correctmath.counterfactual.base-v1conf 100% · 281ms · $0.000 · 811 tok
question
Work strictly in base 13. Add the base-13 numbers B5B and 9BA. Give the result IN BASE 13 (digits beyond 9 are A, B, C). End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1848wrongmath.percent.chain-v2conf 100% · 307ms · $0.000 · 139 tok
question
An inventory starts at 54000 units. The company was founded 180 kilometers from the port. In the first month the inventory grows by 21%. The warehouse was painted 109 years ago. The next month it shrinks by 6%, and the month after it grows by 41%. How many units remain (exact value, round to 2 decimals only if needed)? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
86690.54correctmath.arith.chain-v2conf 100% · 817ms · $0.000 · 346 tok
question
Compute the value of the following expression. (((74 × 96 − 859) × 5 + 9572) − 86 × 18) × 3 End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
117747correctmath.chained.pipeline-v1conf 100% · 293ms · $0.000 · 209 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 17 × 87. Step 2: Q = P × 9 − 624. Step 3: divide Q by 6: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
2117correctmath.percent.chain-v2conf 100% · 266ms · $0.000 · 341 tok
question
An inventory starts at 74000 units. Each pallet weighs about 177 grams more when wet. In the first month the inventory grows by 9%. The company was founded 140 kilometers from the port. The next month it shrinks by 27%, and the month after it grows by 29%. How many units remain (exact value, round to 2 decimals only if needed)? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
75957.52correctmath.arith.chain-v2conf 100% · 288ms · $0.000 · 583 tok
question
Calculate the following. Show your reasoning, then answer. (((87 × 97 − 119) × 6 + 7708) − 47 × 77) × 5 End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
270045correctmath.algebra.system-v2conf 100% · 248ms · $0.000 · 234 tok
question
Solve the system, then answer the derived question. 9x + 6y = -12 7x − 2y = 164 What is the value of 6x − 2y? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
148correctmath.counterfactual.base-v1conf 100% · 580ms · $0.000 · 480 tok
question
Work strictly in base 13. Add the base-13 numbers 52A and 140. Give the result IN BASE 13 (digits beyond 9 are A, B, C). End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
66Acorrectmath.chained.pipeline-v1conf 100% · 294ms · $0.000 · 158 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 18 × 25. Step 2: Q = P × 7 − 349. Step 3: divide Q by 9: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
313wrongmath.percent.chain-v2conf 100% · 1.3s · $0.000 · 191 tok
question
An inventory starts at 97000 units. The delivery van has a 118-liter fuel tank. In the first month the inventory grows by 9%. A rival firm shipped 171 unrelated parcels the same week. The next month it shrinks by 6%, and the month after it grows by 40%. How many units remain (exact value, round to 2 decimals only if needed)? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
139135.08correctmath.algebra.system-v2conf 100% · 290ms · $0.000 · 298 tok
question
Solve the system, then answer the derived question. 2x + 6y = -8 6x − 4y = 218 What is the value of 4x − 5y? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
171correctmath.arith.chain-v2conf 100% · 492ms · $0.000 · 244 tok
question
Work out the exact value of this expression. (((71 × 54 − 635) × 7 + 1586) − 72 × 35) × 2 End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
42918wrongmath.counterfactual.base-v1conf 100% · 257ms · $0.000 · 609 tok
question
Work strictly in base 7. Multiply the base-7 numbers 122 and 125. Give the result IN BASE 7. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1613correctmath.chained.pipeline-v1conf 100% · 266ms · $0.000 · 156 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 36 × 29. Step 2: Q = P × 4 − 368. Step 3: divide Q by 7: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
544correctmath.algebra.system-v2conf 100% · 625ms · $0.000 · 409 tok
question
Solve the system, then answer the derived question. 4x + 6y = -20 2x − 9y = 14 What is the value of 2x − 6y? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
8correctmath.percent.chain-v2conf 100% · 267ms · $0.000 · 278 tok
question
An inventory starts at 68000 units. The warehouse was painted 29 years ago. In the first month the inventory grows by 37%. The warehouse was painted 122 years ago. The next month it shrinks by 40%, and the month after it grows by 42%. How many units remain (exact value, round to 2 decimals only if needed)? End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
79372.32correctmath.arith.chain-v2conf 100% · 275ms · $0.000 · 202 tok
question
Compute the value of the following expression. (((92 × 78 − 860) × 3 + 3603) − 35 × 59) × 6 End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
122916correctmath.chained.pipeline-v1conf 100% · 424ms · $0.000 · 138 tok
question
Solve the following linked steps; each step uses the previous result. Step 1: P = 70 × 34. Step 2: Q = P × 9 − 854. Step 3: divide Q by 4: let q be the integer quotient and r the remainder. The final answer is q + r. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
5143correctmath.counterfactual.base-v1anchorconf 100% · 400ms · $0.000 · 375 tok
model answer:
11236wrongmath.percent.chain-v2anchorconf 100% · 461ms · $0.000 · 300 tok
model answer:
61400.00correctmath.arith.chain-v2anchorconf 100% · 368ms · $0.000 · 230 tok
model answer:
108153correctmath.algebra.system-v2anchorconf 100% · 368ms · $0.000 · 217 tok
model answer:
87multilingual 16/30 correct
correctmultilingual.wordnum-v1conf 100% · 253ms · $0.000 · 182 tok
question
A number is written in French: « huit cent soixante-douze ». Another is written in Spanish: « novecientos sesenta y nueve ». Compute (French number) + (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1841correctmultilingual.wordnum-v1conf 100% · 281ms · $0.000 · 150 tok
question
A number is written in French: « deux cent vingt-cinq ». Another is written in Spanish: « setecientos veintisiete ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-502correctmultilingual.numword-v2conf 100% · 291ms · $0.000 · 27 tok
question
Compute 140 + 219, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
trois cent cinquante-neufwrongmultilingual.numword-v2conf 100% · 250ms · $0.000 · 30 tok
question
Compute 131 + 456, then write the result out in Spanish number words (lowercase). Answer with the Spanish words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
setecientos noventa y sietecorrectmultilingual.wordnum-v1conf 100% · 255ms · $0.000 · 170 tok
question
A number is written in French: « sept cent quatre-vingt-onze ». Another is written in Spanish: « novecientos veintisiete ». Compute (French number) + (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1718correctmultilingual.wordnum-v1conf 100% · 295ms · $0.000 · 172 tok
question
A number is written in French: « deux cent quatre-vingt-huit ». Another is written in Spanish: « ciento veintinueve ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
159wrongmultilingual.numword-v2conf 100% · 293ms · $0.000 · 25 tok
question
Compute 244 + 410, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
quatre cent cinquante-quatrecorrectmultilingual.wordnum-v1conf 100% · 287ms · $0.000 · 157 tok
question
A number is written in French: « quatre cent soixante-seize ». Another is written in Spanish: « ochocientos noventa y uno ». Compute (French number) + (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1367wrongmultilingual.numword-v2conf 100% · 261ms · $0.000 · 29 tok
question
Compute 313 + 182, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
trois cent quatre-vingt-cinqcorrectmultilingual.wordnum-v1conf 100% · 269ms · $0.000 · 183 tok
question
A number is written in French: « quatre cent quatre-vingt-treize ». Another is written in Spanish: « setecientos setenta y uno ». Compute (French number) + (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
1264wrongmultilingual.numword-v2conf 100% · 418ms · $0.000 · 22 tok
question
Compute 187 + 460, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)wrongmultilingual.numword-v2conf 100% · 323ms · $0.000 · 33 tok
question
Compute 462 + 201, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
six cent sixcorrectmultilingual.wordnum-v1conf 100% · 321ms · $0.000 · 33 tok
question
A number is written in French: « huit cent six ». Another is written in Spanish: « ciento sesenta y uno ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
645correctmultilingual.wordnum-v1conf 100% · 284ms · $0.000 · 150 tok
question
A number is written in French: « sept cent trente-deux ». Another is written in Spanish: « novecientos setenta y nueve ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-247correctmultilingual.numword-v2conf 100% · 307ms · $0.000 · 30 tok
question
Compute 450 + 436, then write the result out in Spanish number words (lowercase). Answer with the Spanish words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
ochocientos ochenta y seiscorrectmultilingual.wordnum-v1conf 100% · 268ms · $0.000 · 156 tok
question
A number is written in French: « quatre cent quatre-vingt-onze ». Another is written in Spanish: « novecientos ochenta y tres ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-492wrongmultilingual.numword-v2conf 100% · 382ms · $0.000 · 31 tok
question
Compute 144 + 445, then write the result out in Spanish number words (lowercase). Answer with the Spanish words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
cuatrocientos noventa y nuevewrongmultilingual.numword-v2conf 100% · 666ms · $0.000 · 47 tok
question
Compute 494 + 195, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
six cent quatre-vingt-quatorzecorrectmultilingual.wordnum-v1conf 100% · 335ms · $0.000 · 33 tok
question
A number is written in French: « sept cent trente-sept ». Another is written in Spanish: « trescientos ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
437wrongmultilingual.numword-v2conf 100% · 258ms · $0.000 · 33 tok
question
Compute 438 + 257, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
quatre cent quatre-vingt-quinzecorrectmultilingual.wordnum-v1conf 100% · 302ms · $0.000 · 147 tok
question
A number is written in French: « soixante-treize ». Another is written in Spanish: « ochocientos dieciocho ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-745correctmultilingual.wordnum-v1conf 100% · 263ms · $0.000 · 65 tok
question
A number is written in French: « cent cinquante-deux ». Another is written in Spanish: « ochocientos diez ». Compute (French number) + (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
962wrongmultilingual.numword-v2conf 100% · 344ms · $0.000 · 23 tok
question
Compute 402 + 208, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
quatre cent dixwrongmultilingual.wordnum-v1conf 100% · 256ms · $0.000 · 33 tok
question
A number is written in French: « quatre cent sept ». Another is written in Spanish: « setecientos quince ». Compute (French number) − (Spanish number). Answer with digits only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
-238correctmultilingual.numword-v2conf 100% · 248ms · $0.000 · 29 tok
question
Compute 69 + 303, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
trois cent soixante-douzewrongmultilingual.numword-v2conf 100% · 299ms · $0.000 · 23 tok
question
Compute 176 + 244, then write the result out in French number words (lowercase). Answer with the French words only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
quatre cent soixantecorrectmultilingual.wordnum-v1anchorconf 100% · 263ms · $0.000 · 33 tok
model answer:
150wrongmultilingual.numword-v2anchorconf 100% · 298ms · $0.000 · 27 tok
model answer:
huit cent huitwrongmultilingual.wordnum-v1anchorconf 100% · 306ms · $0.000 · 36 tok
model answer:
6762wrongmultilingual.numword-v2anchorconf 100% · 260ms · $0.000 · 28 tok
model answer:
ochocientos cuarenta y ochoreasoning 27/30 correct
correctreasoning.deduction.position-v1conf 100% · 279ms · $0.000 · 89 tok
question
Four people stand in a queue (number 1 is the front). Emil is directly ahead of Rosa. Liam is directly ahead of Emil. Rosa is directly ahead of Farah. Farah is number 4 in the queue. Who is number 2? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Emilcorrectreasoning.deduction.order-v2conf 100% · 260ms · $0.000 · 274 tok
question
Seven people are ranked by who is faster (rank 1 = fastest). Alice is faster than Liam. Jonas is taller than everyone here, but Jonas is not being ranked. Tessa is faster than Alice. Liam is faster than Priya. Rosa is faster than Mona. Quinn is faster than Mona. Liam is faster than Quinn. Liam is faster than Quinn. Priya is faster than Quinn. Quinn is faster than Rosa. Who is fifth (rank 5)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Quinnwrongreasoning.deduction.order-v2conf 100% · 320ms · $0.000 · 412 tok
question
Seven people are ranked by who is taller (rank 1 = tallest). Tessa is taller than Liam. Tessa is taller than Kira. Tessa is taller than Liam. Kira is taller than Emil. Emil is taller than Mona. Liam is taller than Alice. Mona is taller than Nadir. Nadir is taller than Alice. Ines is older than everyone here, but Ines is not being ranked. Nadir is taller than Liam. Who is third (rank 3)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Nadircorrectreasoning.deduction.position-v1conf 100% · 397ms · $0.000 · 60 tok
question
Four people stand in a queue (number 1 is the front). Ola is number 1 in the queue. Alice is directly ahead of Jonas. Chen is directly ahead of Alice. Who is number 1? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Olacorrectreasoning.deduction.position-v1conf 100% · 255ms · $0.000 · 162 tok
question
Four people stand in a queue (number 1 is the front). Sami is directly ahead of Tessa. Liam is number 2 in the queue. Alice is directly ahead of Liam. Who is number 4? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tessacorrectreasoning.deduction.order-v2conf 100% · 267ms · $0.000 · 239 tok
question
Seven people are ranked by who is heavier (rank 1 = heaviest). Alice is heavier than Farah. Rosa is heavier than Hana. Farah is heavier than Quinn. Quinn is heavier than Hana. Quinn is heavier than Priya. Alice is heavier than Quinn. Emil is heavier than Alice. Alice is heavier than Hana. Sami is faster than everyone here, but Sami is not being ranked. Priya is heavier than Rosa. Who is second (rank 2)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Alicecorrectreasoning.deduction.order-v2conf 100% · 291ms · $0.000 · 293 tok
question
Seven people are ranked by who is faster (rank 1 = fastest). Ines is faster than Rosa. Rosa is faster than Dara. Ines is faster than Dara. Chen is faster than Ola. Liam is faster than Goran. Goran is faster than Chen. Ola is faster than Ines. Tessa is older than everyone here, but Tessa is not being ranked. Ines is faster than Dara. Liam is faster than Ines. Who is second (rank 2)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Gorancorrectreasoning.deduction.position-v1conf 100% · 941ms · $0.000 · 16 tok
question
Four people stand in a queue (number 1 is the front). Chen is number 3 in the queue. Bruno is directly ahead of Chen. Ola is directly ahead of Bruno. Who is number 3? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Chencorrectreasoning.deduction.order-v2conf 100% · 350ms · $0.000 · 289 tok
question
Seven people are ranked by who is heavier (rank 1 = heaviest). Goran is heavier than Farah. Hana is heavier than Dara. Bruno is faster than everyone here, but Bruno is not being ranked. Liam is heavier than Sami. Farah is heavier than Liam. Dara is heavier than Nadir. Nadir is heavier than Liam. Farah is heavier than Nadir. Farah is heavier than Hana. Farah is heavier than Sami. Who is fourth (rank 4)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Daracorrectreasoning.deduction.position-v1conf 100% · 405ms · $0.000 · 17 tok
question
Four people stand in a queue (number 1 is the front). Ola is number 3 in the queue. Bruno is directly ahead of Ola. Tessa is directly ahead of Bruno. Who is number 3? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Olacorrectreasoning.deduction.order-v2conf 100% · 292ms · $0.000 · 298 tok
question
Seven people are ranked by who is taller (rank 1 = tallest). Tessa is taller than Ines. Kira is faster than everyone here, but Kira is not being ranked. Jonas is taller than Quinn. Goran is taller than Ines. Liam is taller than Mona. Mona is taller than Goran. Ines is taller than Quinn. Tessa is taller than Liam. Ines is taller than Jonas. Liam is taller than Ines. Who is fifth (rank 5)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Inescorrectreasoning.deduction.position-v1conf 100% · 309ms · $0.000 · 20 tok
question
Four people stand in a queue (number 1 is the front). Kira is directly ahead of Quinn. Tessa is directly ahead of Kira. Quinn is number 3 in the queue. Who is number 1? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tessacorrectreasoning.deduction.order-v2conf 100% · 271ms · $0.000 · 257 tok
question
Seven people are ranked by who is taller (rank 1 = tallest). Alice is older than everyone here, but Alice is not being ranked. Goran is taller than Emil. Ola is taller than Quinn. Emil is taller than Quinn. Priya is taller than Ola. Emil is taller than Chen. Bruno is taller than Priya. Ola is taller than Emil. Quinn is taller than Chen. Ola is taller than Goran. Who is fourth (rank 4)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Gorancorrectreasoning.deduction.position-v1conf 100% · 288ms · $0.000 · 17 tok
question
Four people stand in a queue (number 1 is the front). Farah is number 2 in the queue. Hana is directly ahead of Farah. Chen is directly ahead of Priya. Who is number 4? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Priyacorrectreasoning.deduction.position-v1conf 100% · 253ms · $0.000 · 16 tok
question
Four people stand in a queue (number 1 is the front). Chen is directly ahead of Hana. Jonas is directly ahead of Chen. Emil is number 1 in the queue. Who is number 3? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Chencorrectreasoning.deduction.order-v2conf 100% · 286ms · $0.000 · 442 tok
question
Seven people are ranked by who is older (rank 1 = oldest). Chen is older than Mona. Dara is older than Mona. Emil is older than Dara. Mona is older than Goran. Ines is older than Chen. Sami is taller than everyone here, but Sami is not being ranked. Mona is older than Bruno. Dara is older than Goran. Dara is older than Ines. Bruno is older than Goran. Who is second (rank 2)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Daracorrectreasoning.deduction.order-v2conf 100% · 268ms · $0.000 · 231 tok
question
Seven people are ranked by who is faster (rank 1 = fastest). Farah is faster than Priya. Priya is faster than Liam. Priya is faster than Quinn. Liam is faster than Dara. Emil is faster than Dara. Liam is faster than Emil. Farah is faster than Chen. Quinn is faster than Chen. Chen is faster than Liam. Mona is heavier than everyone here, but Mona is not being ranked. Who is fifth (rank 5)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Liamcorrectreasoning.deduction.position-v1conf 100% · 305ms · $0.000 · 24 tok
question
Four people stand in a queue (number 1 is the front). Tessa is directly ahead of Goran. Ola is directly ahead of Tessa. Goran is number 3 in the queue. Who is number 1? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Olacorrectreasoning.deduction.order-v2conf 100% · 252ms · $0.000 · 352 tok
question
Seven people are ranked by who is faster (rank 1 = fastest). Goran is faster than Alice. Ola is faster than Bruno. Priya is faster than Goran. Goran is faster than Dara. Priya is faster than Dara. Alice is faster than Ola. Ola is faster than Rosa. Sami is older than everyone here, but Sami is not being ranked. Dara is faster than Rosa. Bruno is faster than Dara. Who is sixth (rank 6)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Daracorrectreasoning.deduction.position-v1conf 100% · 251ms · $0.000 · 20 tok
question
Four people stand in a queue (number 1 is the front). Liam is directly ahead of Dara. Emil is number 1 in the queue. Dara is directly ahead of Goran. Who is number 3? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Daracorrectreasoning.deduction.order-v2conf 100% · 361ms · $0.000 · 535 tok
question
Seven people are ranked by who is heavier (rank 1 = heaviest). Hana is heavier than Priya. Liam is heavier than Jonas. Mona is older than everyone here, but Mona is not being ranked. Chen is heavier than Farah. Priya is heavier than Liam. Priya is heavier than Dara. Farah is heavier than Jonas. Chen is heavier than Liam. Farah is heavier than Liam. Dara is heavier than Chen. Who is second (rank 2)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Priyacorrectreasoning.deduction.position-v1conf 100% · 287ms · $0.000 · 112 tok
question
Four people stand in a queue (number 1 is the front). Tessa is directly ahead of Jonas. Alice is number 4 in the queue. Jonas is directly ahead of Alice. Hana is directly ahead of Tessa. Who is number 2? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tessawrongreasoning.deduction.order-v2conf 100% · 290ms · $0.000 · 269 tok
question
Seven people are ranked by who is heavier (rank 1 = heaviest). Rosa is heavier than Bruno. Bruno is heavier than Chen. Bruno is heavier than Dara. Quinn is heavier than Rosa. Tessa is heavier than Alice. Bruno is heavier than Dara. Alice is heavier than Quinn. Chen is heavier than Dara. Rosa is heavier than Chen. Farah is older than everyone here, but Farah is not being ranked. Who is fifth (rank 5)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Chencorrectreasoning.deduction.position-v1conf 100% · 272ms · $0.000 · 19 tok
question
Four people stand in a queue (number 1 is the front). Priya is directly ahead of Mona. Emil is number 1 in the queue. Mona is directly ahead of Kira. Who is number 1? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Emilcorrectreasoning.deduction.order-v2conf 100% · 262ms · $0.000 · 519 tok
question
Seven people are ranked by who is taller (rank 1 = tallest). Emil is faster than everyone here, but Emil is not being ranked. Mona is taller than Ines. Sami is taller than Farah. Ines is taller than Dara. Kira is taller than Tessa. Tessa is taller than Sami. Ines is taller than Farah. Kira is taller than Ines. Farah is taller than Dara. Sami is taller than Mona. Who is second (rank 2)? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Tessawrongreasoning.deduction.position-v1conf 100% · 300ms · $0.000 · 16 tok
question
Four people stand in a queue (number 1 is the front). Mona is directly ahead of Emil. Emil is number 2 in the queue. Nadir is directly ahead of Ola. Who is number 4? Answer with the name only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
Monacorrectreasoning.deduction.order-v2anchorconf 100% · 291ms · $0.000 · 288 tok
model answer:
Quinncorrectreasoning.deduction.position-v1anchorconf 100% · 262ms · $0.000 · 117 tok
model answer:
Quinncorrectreasoning.deduction.order-v2anchorconf 100% · 407ms · $0.000 · 218 tok
model answer:
Monacorrectreasoning.deduction.position-v1anchorconf 100% · 733ms · $0.000 · 161 tok
model answer:
Farahterminal 8/30 correct
wrongterminal.fs.tree-v1conf 100% · 303ms · $0.000 · 75 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/logs`, `/proj/build`, `/proj/src`): ``` /proj/logs/draft.md /proj/logs/util.log /proj/notes.log /proj/src/setup.txt /proj/todo.md ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mv src/setup.txt src/ mv src/setup.txt src/todo-3.log cd build rm ../../proj/src/todo-3.log mkdir -p ../../proj/logs/src-1 mv ../../proj/logs/util.log ./ cd ../../proj/src cp ../../proj/logs/draft.md ./ cd . ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/build/util.log
/proj/logs/draft.md
/proj/logs/src-1
/proj/logs/util.log
/proj/notes.log
/proj/src/setup.txt
/proj/src/todo-3.log
/proj/src/todo.md
/proj/todo.mdcorrectterminal.exit.chain-v1conf 100% · 305ms · $0.000 · 26 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` data.txt notes.txt ``` `notes.txt` contains exactly the words: amber, dune (one per line). No other files exist. These statements run in order: ```sh test -f ghost.txt && echo A || echo B test -f ghost.txt && echo C || echo D true && echo E || echo F test -f data.txt && echo G || echo H test -f data.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
B
D
E
G
Z
exit:0wrongterminal.pipeline.predict-v1conf 100% · 317ms · $0.000 · 16 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
ivy,hr,36,75
oli,legal,32,43
cy,hr,62,11
max,eng,115,63
ned,hr,36,68
kim,hr,13,33
jon,eng,19,80
lou,legal,25,74
hal,ops,90,10
gus,legal,12,71
```
What is the EXACT stdout of this command?
```sh
grep -F ',eng,' people.csv | awk -F, '{ s += $3 } END { print s }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
214wrongterminal.exit.chain-v1conf 100% · 282ms · $0.000 · 24 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` data.txt notes.txt ``` `notes.txt` contains exactly the words: coral, dune (one per line). No other files exist. These statements run in order: ```sh true && echo A || echo B test -f data.txt && echo C || echo D grep -q basil notes.txt && echo E || echo F true && echo G || echo H test -f ghost.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
C
F
G
exit:0wrongterminal.fs.tree-v1conf 100% · 267ms · $0.000 · 56 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/assets`, `/proj/logs`, `/proj/conf`): ``` /proj/conf/setup.md /proj/logs/index.cfg /proj/logs/util.md /proj/main.log /proj/notes.cfg ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mkdir -p conf/build-4 mkdir -p conf/conf-9 cd conf/build-4 touch ../../../proj/conf/conf-9/main-3.cfg rm ../../../proj/conf/setup.md cp ../../../proj/logs/index.cfg ./ mkdir -p ../../../proj/conf/conf-9/build-3 mkdir -p ../../../proj/build-1 rm ../../../proj/notes.cfg cd ../../../proj/conf ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/conf/conf-9/build-3
/proj/conf/conf-9/main-3.cfg
/proj/conf/index.cfg
/proj/logs/util.md
/proj/main.logwrongterminal.pipeline.predict-v1conf 100% · 271ms · $0.000 · 16 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
dev,legal,44,16
fay,legal,108,39
ivy,legal,112,22
hal,legal,120,19
pam,sales,87,97
eli,eng,33,21
bo,hr,83,19
lou,sales,18,30
ned,sales,108,33
jon,hr,112,81
oli,ops,25,25
```
What is the EXACT stdout of this command?
```sh
grep -F ',eng,' people.csv | awk -F, '{ s += $3 } END { print s }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
135correctterminal.exit.chain-v1conf 100% · 261ms · $0.000 · 24 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt data.txt notes.txt ``` `notes.txt` contains exactly the words: basil, amber (one per line). No other files exist. These statements run in order: ```sh test -f app.txt && echo A || echo B grep -q amber notes.txt && echo C || echo D true && echo E || echo F test -f app.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
C
E
Z
exit:0wrongterminal.fs.tree-v1conf 100% · 276ms · $0.000 · 84 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/assets`, `/proj/build`, `/proj/logs`): ``` /proj/build/draft.log /proj/build/main.log /proj/index.md /proj/logs/setup.md /proj/todo.txt ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh cp build/draft.log assets/ touch logs/main-6.md cd build touch ../../proj/logs/setup-1.cfg touch ../../proj/util-3.log cd . cp ../../proj/logs/setup.md ./ mv setup.md main-3.log cd ../../proj/assets mkdir -p ../../proj/build-9 cd ../../proj/logs ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/assets/build-9
/proj/build/draft.log
/proj/build/main.log
/proj/build/setup-1.cfg
/proj/build/util-3.log
/proj/index.md
/proj/logs/main-6.md
/proj/logs/setup-1.cfg
/proj/logs/setup.md
/proj/todo.txtcorrectterminal.pipeline.predict-v1conf 100% · 267ms · $0.000 · 22 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score): ``` ned,legal,87,68 jon,ops,27,99 max,hr,103,38 kim,eng,8,43 bo,legal,113,36 dev,sales,23,15 hal,sales,119,42 ana,eng,105,82 ivy,ops,97,65 eli,hr,97,20 ``` What is the EXACT stdout of this command? ```sh grep -F ',eng,' people.csv | cut -d, -f1,3 | sort | head -n 3 ``` Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
ana,105
kim,8wrongterminal.fs.tree-v1conf 100% · 514ms · $0.000 · 67 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/build`, `/proj/logs`, `/proj/assets`): ``` /proj/build/todo.cfg /proj/build/util.txt /proj/draft.md /proj/logs/index.txt /proj/setup.log ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mkdir -p build/logs-7 cp setup.log assets/ mkdir -p assets/build-6 cd logs cp index.txt ../../proj/build/logs-7/ cd ../../proj/build mkdir -p ../../proj/assets/assets-2 cd . rm util.txt cd ../../proj/assets/assets-2 cp ../../../proj/setup.log ../../../proj/assets/build-6/ cd ../../../proj/build/logs-7 touch ../../../proj/logs/notes-8.log cd . ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/assets/assets-2/setup.log
/proj/assets/build-6/setup.log
/proj/build/logs-7/index.txt
/proj/draft.md
/proj/logs/notes-8.log
/proj/setup.log
/proj/todo.cfgcorrectterminal.exit.chain-v1conf 100% · 300ms · $0.000 · 26 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt notes.txt ``` `notes.txt` contains exactly the words: basil, amber (one per line). No other files exist. These statements run in order: ```sh true && echo A || echo B grep -q coral notes.txt && echo C || echo D test -f ghost.txt && echo E || echo F true && echo G || echo H test -f app.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
D
F
G
Z
exit:0wrongterminal.pipeline.predict-v1conf 100% · 274ms · $0.000 · 16 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
kim,eng,108,45
gus,eng,88,52
pam,ops,117,56
ned,sales,28,21
max,legal,20,79
cy,ops,101,43
jon,sales,71,21
fay,ops,51,72
ana,sales,10,58
eli,eng,55,10
oli,hr,75,65
bo,sales,109,15
dev,hr,4,55
hal,ops,97,39
```
What is the EXACT stdout of this command?
```sh
grep -F ',ops,' people.csv | awk -F, '{ s += $3 } END { print s }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
377wrongterminal.fs.tree-v1conf 100% · 308ms · $0.000 · 78 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/build`, `/proj/docs`, `/proj/src`): ``` /proj/build/main.log /proj/docs/draft.log /proj/docs/util.cfg /proj/notes.cfg /proj/setup.log ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mv docs/util.cfg docs/report-8.log cd build mv ../../proj/setup.log ../../proj/main-3.cfg touch ../../proj/src/main-5.log touch index-7.txt cd . mv ../../proj/src/main-5.log ./ touch ../../proj/src/notes-5.cfg ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/build/index-7.txt
/proj/build/main-3.cfg
/proj/build/main.log
/proj/docs/draft.log
/proj/docs/report-8.log
/proj/notes.cfg
/proj/setup.log
/proj/src/main-5.log
/proj/src/notes-5.cfgwrongterminal.exit.chain-v1conf 100% · 729ms · $0.000 · 22 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt data.txt notes.txt ``` `notes.txt` contains exactly the words: amber, basil (one per line). No other files exist. These statements run in order: ```sh false && echo A || echo B true && echo C || echo D true && echo E || echo F test -f ghost.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
B
C
E
exit:0wrongterminal.pipeline.predict-v1conf 100% · 402ms · $0.000 · 16 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
lou,legal,5,90
cy,hr,108,20
pam,ops,8,74
dev,legal,107,38
eli,eng,43,58
kim,ops,34,48
ana,legal,29,55
oli,sales,4,68
hal,hr,34,76
ned,sales,43,93
gus,eng,13,47
bo,sales,87,86
ivy,sales,81,22
```
What is the EXACT stdout of this command?
```sh
grep -F ',legal,' people.csv | awk -F, '{ s += $3 } END { print s }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
193wrongterminal.fs.tree-v1conf 100% · 309ms · $0.000 · 100 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/conf`, `/proj/build`, `/proj/docs`): ``` /proj/build/notes.md /proj/build/setup.log /proj/docs/main.md /proj/draft.cfg /proj/todo.txt ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh touch docs/todo-4.txt touch build/notes-4.cfg mkdir -p build/src-4 cp docs/main.md build/ mkdir -p conf/assets-3 cd build mv ../../proj/todo.txt ../../proj/setup-6.cfg mkdir -p src-4/assets-9 ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/build/assets-9
/proj/build/notes-4.cfg
/proj/build/notes.md
/proj/build/setup-6.cfg
/proj/build/setup.log
/proj/build/src-4
/proj/build/src-4/assets-9
/proj/draft.cfg
/proj/docs/main.md
/proj/docs/todo-4.txt
/proj/setup-6.cfg
/proj/todo.txtcorrectterminal.exit.chain-v1conf 100% · 263ms · $0.000 · 24 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt notes.txt ``` `notes.txt` contains exactly the words: dune, amber (one per line). No other files exist. These statements run in order: ```sh test -f app.txt && echo A || echo B test -f tmp.txt && echo C || echo D grep -q basil notes.txt && echo E || echo F test -f app.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
D
F
Z
exit:0wrongterminal.fs.tree-v1conf 100% · 1.1s · $0.000 · 84 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/build`, `/proj/src`, `/proj/logs`): ``` /proj/draft.cfg /proj/index.md /proj/logs/main.txt /proj/logs/report.log /proj/src/todo.txt ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mkdir -p src-3 cp index.md src-3/ mkdir -p logs/conf-5 cd src rm ../../proj/draft.cfg mkdir -p build-1 cd ../../proj/logs/conf-5 touch ../../../proj/build/todo-7.md ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
(none extracted)correctterminal.pipeline.predict-v1conf 100% · 278ms · $0.000 · 14 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
ana,legal,33,21
bo,eng,65,77
jon,ops,36,95
kim,eng,73,71
ned,legal,3,10
fay,sales,43,70
eli,legal,16,22
gus,eng,47,71
pam,eng,47,83
max,legal,96,90
hal,sales,57,19
```
What is the EXACT stdout of this command?
```sh
grep -F ',eng,' people.csv | awk -F, '$4 > 42 { n += 1 } END { print n }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
4wrongterminal.exit.chain-v1conf 100% · 376ms · $0.000 · 22 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` data.txt notes.txt ``` `notes.txt` contains exactly the words: coral, dune (one per line). No other files exist. These statements run in order: ```sh true && echo A || echo B test -f ghost.txt && echo C || echo D grep -q coral notes.txt && echo E || echo F test -f ghost.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
D
E
exit:0wrongterminal.pipeline.predict-v1conf 100% · 304ms · $0.000 · 43 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score): ``` eli,hr,34,96 ned,hr,46,98 pam,sales,94,14 lou,legal,42,18 bo,legal,117,40 kim,legal,80,47 hal,eng,78,61 max,legal,93,39 dev,hr,43,75 oli,hr,96,31 jon,sales,4,48 ivy,eng,62,58 cy,sales,45,43 gus,ops,22,11 ``` What is the EXACT stdout of this command? ```sh grep -F ',legal,' people.csv | sort -t, -k3,3n | tail -n 3 ``` Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
bo,legal,117,40
max,legal,93,39
lou,legal,42,18wrongterminal.fs.tree-v1conf 100% · 321ms · $0.000 · 84 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/docs`, `/proj/conf`, `/proj/assets`): ``` /proj/assets/todo.log /proj/conf/report.md /proj/docs/util.cfg /proj/main.md /proj/notes.txt ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh cp main.md assets/ cd docs mkdir -p ../../proj/docs-5 mkdir -p conf-5 cd conf-5 mv ../../../proj/assets/todo.log ./ mkdir -p ../../../proj/conf/docs-8 cd ../../../proj/conf/docs-8 rm ../../../proj/assets/main.md cd ../../../proj/docs mkdir -p ../../proj/conf/logs-9 cd ../../proj/conf mv ../../proj/notes.txt ../../proj/main-4.log ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/assets/todo.log
/proj/conf/docs-8/../../../proj/assets/todo.log
/proj/conf/logs-9
/proj/conf/main-4.log
/proj/conf/report.md
/proj/docs-5
/proj/docs/util.cfg
/proj/main.md
/proj/notes.txtcorrectterminal.exit.chain-v1conf 100% · 331ms · $0.000 · 24 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt data.txt notes.txt ``` `notes.txt` contains exactly the words: basil, amber (one per line). No other files exist. These statements run in order: ```sh test -f data.txt && echo A || echo B true && echo C || echo D grep -q amber notes.txt && echo E || echo F test -f app.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
C
E
Z
exit:0correctterminal.exit.chain-v1conf 100% · 366ms · $0.000 · 24 tok
question
A POSIX shell session in a directory containing ONLY these files: ``` app.txt data.txt notes.txt ``` `notes.txt` contains exactly the words: amber, basil (one per line). No other files exist. These statements run in order: ```sh test -f app.txt && echo A || echo B grep -q amber notes.txt && echo C || echo D test -f app.txt && echo E || echo F test -f app.txt && echo Z ``` Predict the terminal output: every line printed, in order, then a final line `exit:<N>` where N is the exit status of the LAST statement. Remember: `A && B || C` runs C whenever A fails (it is not a strict if/else); `test -f` succeeds only if the file exists; `grep -q` succeeds only if the word is present. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
A
C
E
Z
exit:0wrongterminal.pipeline.predict-v1conf 100% · 323ms · $0.000 · 14 tok
question
A POSIX shell session (LC_ALL=C). The file `people.csv` contains exactly these lines (columns: name,dept,units,score):
```
cy,eng,89,67
oli,eng,56,11
lou,ops,112,62
kim,sales,11,67
pam,hr,23,60
hal,sales,79,31
bo,sales,5,95
ned,hr,118,87
ana,sales,113,98
fay,sales,62,95
gus,legal,16,71
jon,ops,39,60
```
What is the EXACT stdout of this command?
```sh
grep -F ',ops,' people.csv | awk -F, '$4 > 78 { n += 1 } END { print n }'
```
Notes: plain `sort` compares bytes (so "100" sorts before "9"); `sort -k3,3n` compares field 3 numerically.
Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line:
CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>model answer:
3wrongterminal.fs.tree-v1conf 100% · 595ms · $0.000 · 47 tok
question
A POSIX shell session starts in `/proj`. The tree initially contains these FILES (directories exist as implied, plus empty dirs `/proj/conf`, `/proj/docs`, `/proj/src`): ``` /proj/conf/util.md /proj/docs/setup.cfg /proj/notes.log /proj/report.cfg /proj/src/draft.md ``` These commands run in order (all succeed; `mv x dir/` moves into the directory; paths are relative to the CURRENT working directory, which `cd` changes): ```sh mkdir -p src/src-5 cd conf touch ../../proj/src/src-5/draft-5.txt mkdir -p ../../proj/src/build-5 mkdir -p ../../proj/src/src-5/src-5 touch ../../proj/src/build-5/util-1.txt cd ../../proj rm notes.log mv conf/util.md src/src-5/src-5/ rm src/src-5/draft-5.txt ``` List every file (absolute paths) that exists afterwards, one per line, sorted in byte order (C locale). Do not list directories. Give your final answer inside ONE fenced code block (```), containing exactly the required content and nothing else. After the code block, add one plain-text line: CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
/proj/docs/setup.cfg
/proj/report.cfg
/proj/src/build-5/util-1.txt
/proj/src/src-5/src-5/util.mdwrongterminal.pipeline.predict-v1anchorconf 100% · 342ms · $0.000 · 43 tok
model answer:
cy,eng,115,45
max,eng,43,64
dev,eng,81,95wrongterminal.fs.tree-v1anchorconf 100% · 268ms · $0.000 · 77 tok
model answer:
/proj/build-4/todo-4.md
/proj/build/logs-1/setup.log
/proj/build/logs-8/report-8.cfg
/proj/build/setup-8.md
/proj/docs/util.log
/proj/main.log
/proj/report.cfg
/proj/src/index.cfgwrongterminal.exit.chain-v1anchorconf 100% · 276ms · $0.000 · 24 tok
model answer:
B
D
E
H
exit:0wrongterminal.pipeline.predict-v1anchorconf 100% · 307ms · $0.000 · 14 tok
model answer:
3vision ocr 29/30 correct
correctvision.ocr.table-read-v1conf 100% · 763ms · $0.000 · 75 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
113correctvision.ocr.code-hunt-v1conf 100% · 670ms · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in PURPLE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
TR77JHcorrectvision.ocr.table-read-v1conf 100% · 578ms · $0.000 · 19 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "D". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
141correctvision.ocr.code-hunt-v1conf 100% · 963ms · $0.000 · 21 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in ORANGE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
W9XVFJTMcorrectvision.ocr.code-hunt-v1conf 100% · 1.9s · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in GREEN. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
UTRPDFXFcorrectvision.ocr.table-read-v1conf 100% · 1.1s · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
46wrongvision.ocr.table-read-v1conf 100% · 526ms · $0.000 · 19 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
259correctvision.ocr.code-hunt-v1conf 100% · 745ms · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in RED. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
EVC7C4correctvision.ocr.table-read-v1conf 100% · 653ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
18correctvision.ocr.code-hunt-v1conf 100% · 699ms · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in BLUE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
X9UDE7Acorrectvision.ocr.table-read-v1conf 100% · 481ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
78correctvision.ocr.code-hunt-v1conf 100% · 723ms · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in BLUE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
MRDPM77correctvision.ocr.table-read-v1conf 100% · 631ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
54correctvision.ocr.code-hunt-v1conf 100% · 893ms · $0.000 · 22 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in RED. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
YM3R79ANcorrectvision.ocr.table-read-v1conf 100% · 541ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
55correctvision.ocr.code-hunt-v1conf 100% · 616ms · $0.000 · 20 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in BLUE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
TN4WK9Tcorrectvision.ocr.table-read-v1conf 100% · 557ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
75correctvision.ocr.code-hunt-v1conf 100% · 699ms · $0.000 · 22 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in PURPLE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
U7XC9JTcorrectvision.ocr.table-read-v1conf 100% · 637ms · $0.000 · 19 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the SUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
169correctvision.ocr.code-hunt-v1conf 100% · 712ms · $0.000 · 22 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in PURPLE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
73NDJTP3correctvision.ocr.table-read-v1conf 100% · 447ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "A". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
93correctvision.ocr.code-hunt-v1conf 100% · 601ms · $0.000 · 22 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in BLUE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
PPT79F33correctvision.ocr.table-read-v1conf 100% · 560ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
96correctvision.ocr.code-hunt-v1conf 100% · 714ms · $0.000 · 22 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in RED. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
TNRYW334correctvision.ocr.table-read-v1conf 100% · 445ms · $0.000 · 18 tok
question
The image shows a table with columns ID, QTY, GRADE. Compute the MAXIMUM of QTY over the rows whose GRADE is "C". Answer with the number only. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
67correctvision.ocr.code-hunt-v1conf 100% · 798ms · $0.000 · 19 tok
question
The image contains several printed codes in different colors, with noise. Transcribe EXACTLY the code printed in BLUE. It uses only digits and uppercase letters. End your reply with exactly two plain-text lines (no markdown, no extra text after them): ANSWER: <your final answer only> CONFIDENCE: <integer 0-100, how confident you are that your answer is correct>
model answer:
FAVJTFcorrectvision.ocr.table-read-v1anchorconf 100% · 623ms · $0.000 · 18 tok
model answer:
15correctvision.ocr.code-hunt-v1anchorconf 100% · 661ms · $0.000 · 22 tok
model answer:
VX7993Dcorrectvision.ocr.code-hunt-v1anchorconf 100% · 1.3s · $0.000 · 22 tok
model answer:
YH9E4AWPcorrectvision.ocr.table-read-v1anchorconf 100% · 742ms · $0.000 · 18 tok
model answer:
25Run history
- 2026-08-05v0.2.0index_fit506
- 2026-08-05v0.2.0index_fit506
- 2026-08-05v0.2.0index_fit506
- 2026-08-05v0.2.0index_fit506
- 2026-08-05v0.2.0index_fit507
- 2026-08-05v0.2.0index_fit507
- 2026-08-05v0.2.0index_fit510
- 2026-08-05v0.2.0index_fit510
- 2026-08-05v0.2.0index_fit513
- 2026-08-05v0.2.0index_fit513
- 2026-08-05v0.2.0index_fit515
- 2026-08-05v0.2.0index_fit516
- 2026-08-05v0.2.0index_fit513
- 2026-08-05v0.2.0index_fit512
- 2026-08-05v0.2.0index_fit512
- 2026-08-05v0.2.0index_fit513
- 2026-08-05v0.2.0index_fit515
- 2026-08-05v0.2.0index_fit515
- 2026-08-05v0.2.0index_fit514
- 2026-08-05v0.2.0index_fit514