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thienanblogthienanblog/awesome-ai-agent-skills/skills/debugging-workflow/SKILL.md

debugging-workflow

Skill68 starsChanged 7 months agoApache-2.0View on GitHub

Reproduce, isolate, and fix unexplained failures, regressions, or flaky behavior. Use when the cause is uncertain; a known-cause fix usually needs only the normal implementation workflow.

2 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    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:

    Use evidence to locate the failing boundary and fix the cause while preserving business intent.

    line 8
  2. Distinctive:

    Run in the main conversation by default.

    line 12
  3. Distinctive:

    Read debugging-playbook.md for deeper isolation, flaky failures, or temporary instrumentation.

    line 21
  4. Distinctive:

    If measurement or test design becomes the main work, consult the relevant specialist guidance directly when available.

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

Debugging Workflow

Use evidence to locate the failing boundary and fix the cause while preserving business intent.

Delegation

Run in the main conversation by default. Delegation can increase usage: obtain explicit approval for the proposed agent count and scope before using subagents. Reuse that approval within its bounds; ask again before expanding the approved count or scope.

Investigate

  1. Capture the failing command or flow, input, expected behavior, actual result, and relevant environment. Read the error and nearby source before expanding the search.
  2. Reproduce the smallest useful case when practical. If reproduction is unavailable, distinguish what logs or source prove from what remains a hypothesis.
  3. Trace the symptom through the affected boundaries. Choose checks that distinguish plausible causes; independent observations can run together when safe. Avoid stacking speculative fixes.
  4. For a UI failure, inspect the supplied image or rendered state. Annotate a copy only if that makes a material ambiguity easier to resolve.

Read debugging-playbook.md for deeper isolation, flaky failures, or temporary instrumentation. Keep sensitive data out of logs and remove temporary debug code.

Fix and verify

Make the smallest coherent fix, preserving unusual business rules unless evidence shows they are the defect. Avoid unrelated refactors. Add a regression test when it provides durable protection, ideally demonstrating failure before the fix.

Rerun the original failure and affected checks. Complete repository-required checks; broaden only when a remaining risk warrants it and authorization permits. Reuse results that remain valid.

If measurement or test design becomes the main work, consult the relevant specialist guidance directly when available.

Report

Explain the cause, fix, and evidence that the failure is resolved. Include reproduction limits or remaining uncertainty. Record a difficult bug in existing durable docs only when future work would benefit.

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