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imMamdouhaboammarimMamdouhaboammar/get-things-done/.claude/skills/debug-issue/SKILL.md

debug-issue

Skill2 starsChanged 2 months agoMITView on GitHub

Systematically debug issues using graph-powered code navigation

17 other projects use a version of this, 2 of them edited.

Adopted by

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Used with

Projects with it also use refactor-code, reverse-engineer and 4 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 4 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 16 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use the knowledge graph to systematically trace and debug issues.

    line 8
  2. Very specific:

    Use semantic_search_nodes_tool to find code related to the issue.

    line 12
  3. Very specific:

    Use query_graph_tool with callers_of and callees_of to trace call chains.

    line 13
  4. Very specific:

    Use get_flow_tool to see full execution paths through suspected areas.

    line 14
  5. Very specific:

    Run detect_changes_tool to check if recent changes caused the issue.

    line 15
  6. Very specific:

    Use get_impact_radius_tool on suspected files to see what else is affected.

    line 16
  7. Distinctive:

    Check both callers and callees to understand the full context.

    line 20
  8. Distinctive:

    Look at affected flows to find the entry point that triggers the bug.

    line 21
  9. Very specific:

    Start with get_minimal_context_tool(task="<your task>") before other graph tools.

    line 25
  10. Very specific:

    Use detail_level="minimal" on all calls.

    line 26
  11. Distinctive:

    Read the implementation and its tests before changing code.

    line 28

“Common” is measured: kept by at least 6 in 10 of the 16 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

Debug Issue

Use the knowledge graph to systematically trace and debug issues.

Steps

  1. Use semantic_search_nodes_tool to find code related to the issue.
  2. Use query_graph_tool with callers_of and callees_of to trace call chains.
  3. Use get_flow_tool to see full execution paths through suspected areas.
  4. Run detect_changes_tool to check if recent changes caused the issue.
  5. Use get_impact_radius_tool on suspected files to see what else is affected.

Tips

  • Check both callers and callees to understand the full context.
  • Look at affected flows to find the entry point that triggers the bug.
  • Recent changes are the most common source of new issues.

Token Efficiency Rules

  • Start with get_minimal_context_tool(task="<your task>") before other graph tools.
  • Use detail_level="minimal" on all calls. Only escalate to "standard" when minimal is insufficient.
  • Target: complete any review/debug/refactor task in ≤5 tool calls and ≤800 total output tokens.
  • Read the implementation and its tests before changing code. The graph narrows scope; it does not replace the source.

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