# Skill Dependency Fan Out Inspector

> Inspect skill-to-skill dependencies and detect fan-out, cycles, and N+1 invocation risk. Use when scaling skill stacks or diagnosing hidden cross-skill cost/latency amplification.

- Skill: `grtninja/skill-dependency-fan-out-inspector` (Agent Skill, multi-file: 5 files)
- Install (CLI): `npx skillmds@latest add grtninja/skill-dependency-fan-out-inspector`
- Raw SKILL.md: https://api.skillmd.com/api/skills/grtninja/skill-dependency-fan-out-inspector/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: grtninja (https://skillmd.com/u/grtninja)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/grtninja/skill-dependency-fan-out-inspector

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# Skill Dependency Fan-Out Inspector

Use this skill to make cross-skill invocation risk explicit before it causes cost or latency blowups.

## Workflow

1. Scan skill metadata under `skill-candidates/`.
2. Build a dependency graph from explicit `$skill-name` references.
3. Flag fan-out hotspots, high transitive reach, and cycles.
4. Emit JSON and optional DOT graph artifacts.

## Inspect Graph

```bash
python3 "$CODEX_HOME/skills/skill-dependency-fan-out-inspector/scripts/dependency_inspector.py" \
  --skills-root skill-candidates \
  --fanout-threshold 4 \
  --transitive-threshold 12 \
  --json-out /tmp/skill-dependency-report.json \
  --dot-out /tmp/skill-dependency-graph.dot \
  --format table
```

Use `--include-plain-names` when legacy skills mention dependencies without `$` prefixes.
## Scope Boundary

Use this skill only for the `skill-dependency-fan-out-inspector` lane and workflow defined in this file and its references.

Do not use this skill for unrelated lanes; route those through `$skill-hub` and the most specific matching skill.

## References

- `references/inspection-workflow.md`
- `references/graph-contract.md`

## Loopback

If this lane is unresolved, blocked, or ambiguous:

1. Capture current evidence and failure context.
2. Route back through `$skill-hub` for chain recalculation.
3. Resume only after the updated chain returns a deterministic next step.