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Systematic failure mode cataloging — generate boundary inputs, observe failures, cluster by mechanism, identify triggers, estimate frequency.
Passed 15 of 21 test cases with the skill, and 12 of 21 without it.
and 4 more in the full report
7 fixed9 passed either way2 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are preparing to deploy an automated contract analysis system and need to map out potential breakdown points before launch. Please stress-test this pipeline by simulating extreme inputs, distribution shifts, and rare boundary scenarios, then group the resulting system breakdowns by their underlying root mechanisms rather than surface symptoms, detailing the precise trigger conditions for each identified group.
| Checked | Without skill | With skill |
|---|---|---|
| The response presents at least 20 distinct generated edge cases or stress scenarios. | Missed | Passed |
| The response categorizes failures into at least 3 distinct failure clusters based on underlying root mechanisms. | Passed | Passed |
| The response specifies at least one concrete trigger condition for each identified failure cluster. | Passed | Passed |
The instructions your model reads when the skill loads.
Build a comprehensive failure taxonomy.
Subagent: edge-case-generation, failure-clustering, scaling-regime-detection Import: web-search
Generate edge cases systematically (boundary values, adversarial inputs, distribution shifts, scale extremes), observe which cause failures, cluster failures by mechanism, identify common triggers.
<HARD-GATE>
- edge cases generated: >= 20
- failure clusters identified: >= 3
- triggers per cluster: >= 1
</HARD-GATE>
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| deep-insight-web-search | Quick web scanning for landscape understanding. Import of web-browsing/web-search skill. Snippets only — no conclusions from snippets alone. |
| edge-case-generation | Systematically generate boundary inputs — boundary values, adversarial constructions, distribution shifts, rare combinations, scale extremes. |
| failure-clustering | Group observed failures by mechanism (not symptom), identify common triggers per cluster, estimate frequency and severity. |
| scaling-regime-detection | Detect regime changes in scaling behavior — breakpoints where behavior qualitatively shifts, mechanisms behind transitions. |
test cases passed, vs 12 / 21 without
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