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neuraforge-cl-esneuraforge-cl-es/adaptive-engineering/skills/systematic-debugging/SKILL.md

systematic-debugging

Skill1 starsChanged 11 days agoMITView on GitHub

Debug failures by reproducing, narrowing, forming evidence-based hypotheses, and verifying the root cause before applying the smallest durable fix.

190 other projects use a version of this.

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Projects with it also use chinese-code-review, chinese-commit-conventions and 10 more.

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The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 177 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Test the cheapest discriminating hypothesis first.

    line 13
  2. Distinctive:

    Add a regression test when it protects meaningful behavior.

    line 16
  3. Distinctive:

    Verify both the original failure path and nearby success paths.

    line 17

“Common” is measured: kept by at least 6 in 10 of the 177 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Systematic Debugging

Workflow

  1. Reproduce the failure or gather the strongest available evidence.
  2. State observed behavior separately from assumptions.
  3. Reduce the failing surface: input, boundary, component, environment, or commit.
  4. Form one or a small number of falsifiable hypotheses.
  5. Test the cheapest discriminating hypothesis first.
  6. Identify the root cause, not merely a symptom.
  7. Implement the smallest durable fix.
  8. Add a regression test when it protects meaningful behavior.
  9. Verify both the original failure path and nearby success paths.

Avoid

  • random edits followed by reruns
  • broad refactors during diagnosis
  • changing multiple suspected causes at once
  • adding retries/timeouts without understanding the failure
  • swallowing errors to make tests green

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