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Execute one bounded RED to GREEN experiment
Passed 14 of 19 test cases with the skill, and 8 of 19 without it.
and 7 more in the full report
8 fixed8 passed either way5 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
After applying changes to `net/http_client.py`, the targeted check fails with exit code 1. Should you enter a validation loop or build a retry packet?
| Checked | Without skill | With skill |
|---|---|---|
| The response treats the failed check strictly as factual evidence to return to the caller without initiating validation loops or candidate packets | Missed | Passed |
The instructions your model reads when the skill loads.
Execute exactly one bounded experiment described by the resolved bead or caller intent. Implement owns subject edits and factual evidence. It does not create a second planning record or a model-authored candidate packet.
subject-manifest.v1 from
the before/after subject. Do not make the model transcribe those facts.Specialists such as standards, domain, test, refactor, and security may provide advice. They are never hard dependencies and cannot add lifecycle authority.
During edits, run the smallest deterministic checks that can falsify the active change. Reuse exact-input receipts when their subject and tool identity still match. Run an expensive full-suite check at the integration boundary, or earlier only when the intent explicitly makes it the first acceptance check. Repeatedly replaying the full suite after every focused edit adds latency, not proof.
On discovering a live consumer of the change outside the declared write scope — a test asserting the old path, a generated twin, a gate reading the moved
test cases passed, vs 8 / 19 without
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