athola/skill-graph-audit
Audit Skill() refs; detect hubs, isolates, and dangling targets. Use when auditing skills.
npx skills add https://github.com/athola/claude-night-market --skill skill-graph-audit
Build a directed graph of Skill(plugin:name) invocations across the
marketplace and surface composition patterns: which skills are heavily
referenced (hubs), which orchestrate many others (orchestrators), which
have no incoming or outgoing references (isolates), and which point at
non-existent skills (dangling references).
The federation graph is now derivable from source rather than
hand-curated.
Skill() referencesSkill(abstract:skills-eval) insteadSkill(abstract:plugin-review)Skill(abstract:hooks-eval)python3 plugins/abstract/scripts/skill_graph.py \
--plugins-root plugins --top-n 10
For machine-readable output:
python3 plugins/abstract/scripts/skill_graph.py \
--plugins-root plugins --format json --output reports/skill-graph.json
See modules/usage.md for full CLI reference and example workflows.
| Output | Meaning | Action when high |
|--------|---------|------------------|
| Hubs | Most-referenced skills | Treat as core API; retire with extreme care |
| Orchestrators | Skills that call many others | Verify each ref still resolves |
| Isolates | Zero in / zero out | Check role: library? entrypoint? typo? |
| Dangling: bugs | Missing internal target | Fix immediately (typo or retired skill) |
| Dangling: external | Reference to external plugin | Document plugin dependency |
| Dangling: placeholders | Template text like -NAME | Verify intentional |
See modules/interpretation.md for false-positive guidance and
isolation taxonomy.
This skill itself was scaffolded TDD-first; on first run against
plugins/, it caught two genuine dangling refs that the manual
audit (2026-04-25) had missed:
attune:makefile-generation -> abstract:makefile-dogfooder(script name confused with skill name)
imbue:karpathy-principles -> spec-kit:speckit-clarify(command referenced as skill)
Both were converted to correct command-style references in the
same session.
Two ways to validate the audit output is trustworthy:
plugins/abstract/tests/scripts/test_skill_graph.py` to confirm
extraction, graph construction, ranking, isolate detection, and
dangling-ref classification all pass on the current code. The
-o addopts= flag bypasses the package-wide coverage gate, which
would otherwise fail on a single-file run.
baseline run, fix one or more flagged references, then rerun and
verify the count drops by at least the number fixed. If the count
does not move, the report is stale or the regex missed a syntax
variant.
skill_graph.py runs against plugins/without error and emits a node/edge count.
placeholders (the three Core Outputs rows resolve).
Dangling: bugs entry is either fixed in the samesession or filed as a tracked issue.
pytest -o addopts= plugins/abstract/tests/scripts/test_skill_graph.pypasses.
by at least the number of references fixed.
Skill(abstract:skills-eval): per-skill quality scoringSkill(abstract:plugin-review): plugin manifest and structureSkill(abstract:hooks-eval): hook-specific validationSkill(abstract:rules-eval): rules directory validationplugins/abstract/scripts/skill_graph.pyplugins/abstract/tests/scripts/test_skill_graph.pydocs/quality-gates.md#skill-level-quality-gate-composition
docs/skill-integration-guide.md#skill-role-taxonomyTake athola/skill-graph-audit from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.