debugging

Solid

Systematic debugging of issues — use when a test fails, runtime error occurs, unexpected behavior is reported, or an awareness tick produces anomalous results

AI & Automation 77 stars 13 forks Updated today MIT

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Skill Content

# Debugging ## Purpose Systematically diagnose and resolve bugs, failures, or unexpected behavior in Genesis or its dependencies. ## When to Use - A test fails unexpectedly. - Runtime error or unexpected behavior is reported. - An awareness tick or reflection produces anomalous results. - Obstacle resolution escalates a technical issue. ## Workflow 1. **Reproduce** — Confirm the issue. Get the exact error, stack trace, or unexpected output. Define "expected vs. actual." 2. **Isolate** — Narrow the scope. Which module? Which function? Which input triggers it? Use binary search on the call chain. 3. **Hypothesize** — Form 2-3 candidate explanations. Rank by likelihood. 4. **Test hypotheses** — Write a minimal test or add logging to confirm/deny each hypothesis. Start with the most likely. 5. **Fix** — Apply the minimal correct fix. Do not fix adjacent issues in the same change. 6. **Verify** — Run the failing test. Run the full test suite. Confirm no regressions. 7. **Document** — Record the root cause and fix as an observation. Update procedures if the bug class is recurring. ## Output Format ```yaml issue: <one-line description> date: <YYYY-MM-DD> root_cause: <what actually went wrong> fix: <what was changed> files_modified: - <file path> regression_risk: low | medium | high lesson: <what to remember to prevent recurrence> ``` ## Examples ### Example: Hook fails in non-login shell **Trigger:** Post-commit hook throws `KeyError: 'HOME'` in CI-lik...

Details

Author
WingedGuardian
Repository
WingedGuardian/GENesis-AGI
Created
2 months ago
Last Updated
today
Language
Python
License
MIT

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