AugmentClaude
BackendTesting

Debug Issue

By tirth8205· tirth8205/code-review-graph· 0

Trace and debug code issues using semantic search and execution flow analysis.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.
    Install
    Sign up to copy
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    This copies the whole skill folder into ~/.claude/skills/debug-issue-tirth8205/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
    Sign up to copy
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  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Systematically debug issues using graph-powered code navigation

What this skill does

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 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

  • ALWAYS start with get_minimal_context(task="<your task>") before any other graph tool.
  • 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.

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