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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.

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SKILL.md (original)

Review the instructions the agent will receive before you install.

Call Chain Tracing

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

When NOT To Use

  • Static import relationships (use cartograph:dependency-graph)
  • Scoring the risk of a change (use pensive:blast-radius)

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

FactorWeightMeaning
File spread0.30Touches many files
Security0.25Contains auth/crypto code
External calls0.20Unresolved dependencies
Test gap0.15Untested nodes in flow
Depth0.10Deep call chains

Exit Criteria

  • Indented call tree displayed for the target function with criticality scores in the form [criticality: N.NN]
  • Mermaid flowchart LR generated with edges representing each caller-to-callee relationship in the traced path
  • Criticality breakdown table shown covering: file spread, security sensitivity, external calls, test gap, and depth
  • If gauntlet is not installed, fallback to static rg/grep analysis is used and the absence of graph data is noted
  • If gauntlet is installed but graph.db is absent, user is told to run /gauntlet-graph build before the skill halts

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