> Night Market Skill — ported from claude-night-market/cartograph. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

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).

1. Run flow tracing (requires gauntlet):

```bash

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

```

To filter by entry point:

```bash

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

```

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

```bash

# 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.

1. Display as indented tree:

```

main() [criticality: 0.72]

-> validate_input()

-> parse_config()

-> process_data()

-> db.execute_query()

-> cache.store()

-> send_response()

```

1. Generate Mermaid flowchart:

```mermaid

flowchart LR

main --> validate_input

main --> process_data

main --> send_response

validate_input --> parse_config

process_data --> db.execute_query

process_data --> cache.store

```

1. 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