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Standardize evaluation condition differences across papers — 20 methods, 60 data points, 30 web searches budget
Passed 2 of 18 test cases with the skill, and 3 of 18 without it.
0 fixed3 passed either way19 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
The instructions your model reads when the skill loads.
Papers evaluate methods under different conditions (data splits, preprocessing, hardware, hyperparameter budgets). This strategy identifies condition differences, builds a normalization scheme, and produces fair-comparison baselines where results are adjusted to equivalent conditions.
| Resource | Floor | Target |
|---|---|---|
| Methods analyzed | 15 | 20 |
| Data points standardized | 40 | 60 |
| Web searches | 20 | 30 |
| Condition dimensions cataloged | 5 | 10 |
<HARD-GATE>
| Metric | Current | Target | Status |
|--------|---------|--------|--------|
| Methods analyzed | 0 | 20 | BLOCKED |
| Data points standardized | 0 | 60 | BLOCKED |
| Condition dimensions | 0 | 10 | — |
| Normalization rules defined | 0 | 5 | — |
| Fair comparison sets | 0 | 3 | — |
</HARD-GATE>
Cannot exit until data_points_standardized >= 48 (80% of target).
test cases passed, vs 3 / 18 without
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