Debugging
Systematic debugging with drift checks: spec vs code, outdated handoff, reproduce, narrow, minimal fix.From its SKILL.md
npx -y skills add LaProgrammerie/ai-engineering-core --skill debuggingAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
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Debugging (global)
Objective
Find root cause with a reproducible method, then propose a minimal verifiable fix.
When to use
- Failing tests, runtime errors, flaky behaviour
- Incident analysis (read-only mode if required)
Expected inputs
- Exact symptom (message, stack, screenshot)
- Environment, version, reproduction steps
- Suspected recent changes (if known)
- Logs or traces available
Steps
- Reproduce with a minimal scenario; if impossible, list what is missing.
- Narrow: bisect in time (commits) or space (modules).
- Hypotheses: rank by likelihood; disprove with evidence (logs, tests, experiments).
- Fix: target root cause; avoid expensive band-aids when a cleaner fix is reasonable.
- Harden: suggest a small test, assertion, or log to prevent recurrence.
Drift checks (behaviour mismatch)
When behaviour does not match expectations:
- Check for spec vs implementation drift (
.kiro/specs/or equivalent vs code). - Check whether
docs/ai/active/handoff.md(or equivalent) is stale relative to what was actually built. - If docs are wrong, recommend updating spec / handoff / projections — not only patching code to match outdated text.
Output format
- Current theory + evidence for / against
- Proposed fix (or options if uncertain)
- Verification steps (commands or scenarios)
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.