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Map which assumptions are load-bearing by assessing how the conclusion changes if each assumption fails.
Passed 19 of 22 test cases with the skill, and 19 of 22 without it.
1 fixed19 passed either way2 still failing1 broke
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A test case the skill fixed. Same model, same prompt, with and without the skill.
A logistics company is assessing whether to deploy an autonomous truck fleet based on six complex, interconnected regulatory, hardware reliability, and labor agreement assumptions. The analyst is tempted to evaluate each assumption in a separate isolated prompt thread to avoid context overload. Specify the optimal execution structure for evaluating these interconnected assumptions when conducting a sensitivity assessment.
| Checked | Without skill | With skill |
|---|---|---|
| The output specifies executing the analysis via a subagent with access to all assumptions simultaneously. | Missed | Passed |
The instructions your model reads when the skill loads.
Maps the relationship between assumptions and conclusions — identifying which assumptions are load-bearing (conclusion changes if they fail) versus decorative (conclusion holds regardless). Produces a sensitivity map for decision-makers.
Spawns a subagent that takes all extracted assumptions and their challenges, then maps conclusion sensitivity to each.
Output must include:
Optional, no fixed order; the final leaf is always a sop.
| SOP | When to use |
|---|---|
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |
test cases passed, vs 19 / 22 without
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