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This skill should be used when verifying documentation claims against codebase reality.
Passed 16 of 22 test cases with the skill, and 10 of 22 without it.
and 4 more in the full report
7 fixed10 passed either way6 still failing0 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 running a doc audit on the 'AppCore' repository on October 24, 2024. What exact file path and filename must the audit report be saved to?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies output path `docs/audits/AUDIT_REPORT_2024-10-24.md` | Missed | Passed |
The instructions your model reads when the skill loads.
Systematically verify claims in documentation against the actual codebase using a two-pass approach.
Core principle: Low recall is worse than false positives—missed claims stay invisible.
Two-pass process:
plans/, audits/)docs/audits/AUDIT_REPORT_YYYY-MM-DD.md| Type | Example | Verification |
|---|---|---|
file_ref | scripts/foo.py | File exists? |
config_default | "defaults to 'AI Radio'" | Check schema/code |
env_var | STATION_NAME | In .env.example + code? |
cli_command | --normalize flag | Script supports it? |
behavior | "runs every 2 minutes" | Check timers/code |
Verification confidence:
test cases passed, vs 10 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.