Thin material, no room to skip judgement
Two worksheets, 8.5 KB, no cross-checking source. Every conclusion has to come from these two series; anything missing becomes a stated assumption or limitation.
KTHY-FIN-MEMO-9211 · Operating plan · operating profit path · household position
Two worksheets only: one operating profit and margin path, one commitment and growth series. Join the two to judge how far the operating plan supports earnings, give an explicit position recommendation with its evidence strength, and add quantified sensitivity.
Two worksheets, 8.5 KB, no cross-checking source. Every conclusion has to come from these two series; anything missing becomes a stated assumption or limitation.
The workbook, the memo and the JSON must carry the same headline conclusions, and key derived figures must be formulas that reference the source data inside the workbook.
The instruction asks for a recommendation plus its evidence strength. Separating what you verified from what you infer is itself a scoring point.
Three models answered under the same criteria for a mean of 0.5811. With only two worksheets, every run finished inside 20 turns: the test is judgement, not retrieval.
An excerpt of the instruction the agent actually receives, showing the task setup and constraints.
You are a family financial planner at a family office. The client household is discussing its position in an e-commerce platform listed in Hong Kong; your conclusion decides whether the household buys, adds, or holds, and roughly how much to allocate.
Build an earnings judgement that can support the investment discussion from the material provided, and clearly label source facts, your own calculations and your judgement.
NOTEEnglish translation of the original Chinese instruction; the workbook blocks, the five memo sections and the JSON key requirements are omitted.
Everything visible inside the agent container, with statistics generated from the task package. Original files ship with the full sample package.
| File | Type | Size | Bytes |
|---|---|---|---|
| KTHY_业务底稿.xlsxOperating workpaper: operating profit and margin path (2019A–2028E), commitments and revenue growth including the quarterly series | xlsx | 2 sheets | 8 KB |
Full criteria text, weights and reference answers ship with the complete data package.
Trajectory statistics from frontier models in real agent harnesses. One turn is one model call; the context curve shows how state accumulates over a long-horizon task.
| Model | Agent turns | Tool calls | Cumulative prompt tokens | Peak context | Time | Result |
|---|---|---|---|---|---|---|
| Claude Opus 4.8Claude Code · Harbor | 12 | 703K | 74K | — | Completed | |
| GPT-5.6-solCodex · Harbor | 14 | 413K | 35K | — | Completed | |
| Qwen3.8-MaxClaude Code · Harbor | 13 | 555K | 53K | — | Completed |
| Task ID | KTHY-FIN-MEMO-9211 |
|---|---|
| Task format | Harbor task.toml · schema 1.4 |
| Package version | 1.0.0 |
| Agent time limit | 3 h |
| Verifier time limit | 5 h |
| Agent container | 2 vCPU · 8 GB memory · 30 GB storage |
| Network | Only for agent harness installation |
| Tool set | filesystem · shell · python |
| Scoring isolation | Separate verifier containerJudge credentials are injected only into the verifier and are invisible to the agent |
| Instruction length | 1,515 characters |
| Difficulty | A2 (three-model mean 0.5811) |
| Reference solution | oracle reward 1.000 |
| Material size | 2 worksheets · annual and quarterly series |
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