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Call Chain

  • 76 installs
  • 325 repo stars
  • Updated August 2, 2026
  • athola/claude-night-market

Trace how a function or entry point fans out through your codebase with scored paths and a Mermaid flow chart before refactoring or debugging.

About

Call Chain is an agent skill for solo builders who need to see how execution actually moves through their repo—not just a single file. It targets a function name or entry point, then uses the gauntlet plugin’s graph_query tool to trace flows up to depth 15, apply criticality scoring, and render Mermaid charts from the code knowledge graph. When gauntlet is not installed, the skill explicitly falls back to ripgrep or grep to reconstruct call trees from import and invocation patterns so you are never blocked from a diagram. It fits greenfield navigation, pre-refactor reconnaissance, and understanding blast radius before changing shared utilities. You run it when a symptom points at one function but the real behavior spans layers. Intermediate complexity: you need either a built graph.db or comfort reading search hits into a manual tree.

  • Runs gauntlet graph_query.py flows with configurable depth and optional entry-point filter
  • Scores criticality on traced paths for prioritizing review or incident triage
  • Outputs Mermaid diagrams from the code knowledge graph
  • Degrades to rg/grep static call tracing when gauntlet is missing
  • Documents prerequisite: build graph with /gauntlet-graph build when graph.db is absent

Call Chain by the numbers

  • 76 all-time installs (skills.sh)
  • Ranked #259 of 596 Debugging skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/athola/claude-night-market --skill call-chain

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Listed on Skillselion
Installs76
repo stars325
Security audit2 / 3 scanners passed
Last updatedAugust 2, 2026
Repositoryathola/claude-night-market

What it does

Trace how a function or entry point fans out through your codebase with scored paths and a Mermaid flow chart before refactoring or debugging.

Files

SKILL.mdMarkdownGitHub ↗

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

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

Related skills

FAQ

Is Call Chain safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Debuggingbackendtesting

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