Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →yogsoth-ai/conclusion-sensitivity-measurement
Quantify how much conclusions change across all assumption negations and produce a sensitivity ranking.
Passed 13 of 20 test cases with the skill, and 3 of 20 without it.
and 8 more in the full report
11 fixed4 passed either way9 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
In the structured SOP hierarchy for this workflow, what type of component must always serve as the final leaf node?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies that the final leaf node is always a sop. | Missed | Passed |
The instructions your model reads when the skill loads.
Subagent — spawned via subagent-spawning/spawn-agent.
One unit = one complete sensitivity measurement and ranking across all tested assumptions.
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 3 / 20 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.