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call-chain

Traces execution paths through the code graph with criticality scoring and Mermaid charts. Use when understanding how a function propagates through the system.

Stars
294
Source
athola/claude-night-market
Updated
2026-05-30
Slug
athola--claude-night-market--call-chain
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/athola/claude-night-market/HEAD/plugins/cartograph/skills/call-chain/SKILL.md -o .claude/skills/call-chain.md

Drops the SKILL.md into .claude/skills/call-chain.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

Call Chain Tracing

Trace execution flows through the codebase using the code knowledge graph.

Prerequisites

This skill requires the gauntlet plugin for graph data. Discover it:

GRAPH_QUERY=$(find ~/.claude/plugins -name "graph_query.py" -path "*/gauntlet/*" 2>/dev/null | head -1)

If gauntlet is not installed: Fall back to static analysis. Use grep to trace function calls and build a Mermaid diagram manually from import/call patterns. Skip graph-specific steps.

If installed but no graph.db: Tell the user to run /gauntlet-graph build.

Steps

  1. Accept target: Get a function name or entry point from the user (or trace all entry points).

  2. Run flow tracing (requires gauntlet):

    python3 "$GRAPH_QUERY" --action flows --depth 15
    

    To filter by entry point:

    python3 "$GRAPH_QUERY" --action flows --entry "main"
    

    Fallback (no gauntlet): Trace calls with rg (or grep):

    # Prefer rg (ripgrep) for speed; fall back to grep
    if command -v rg &>/dev/null; then
      rg -n "function_name\(" --type py . | head -20
    else
      grep -rn "function_name(" --include="*.py" . | head -20
    fi
    

    Build the call tree manually from search results.

  3. Display as indented tree:

    main() [criticality: 0.72]
      -> validate_input()
        -> parse_config()
      -> process_data()
        -> db.execute_query()
        -> cache.store()
      -> send_response()
    
  4. Generate Mermaid flowchart:

    flowchart LR
      main --> validate_input
      main --> process_data
      main --> send_response
      validate_input --> parse_config
      process_data --> db.execute_query
      process_data --> cache.store
    
  5. Show criticality breakdown:

    • File spread: how many files the flow touches
    • Security sensitivity: auth/crypto code in the path
    • Test coverage gaps: untested nodes in the flow

Criticality Scoring

Factor Weight Meaning
File spread 0.30 Touches many files
Security 0.25 Contains auth/crypto code
External calls 0.20 Unresolved dependencies
Test gap 0.15 Untested nodes in flow
Depth 0.10 Deep call chains