athola Skill Graph Audit
Overview
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.
When To Use
- Before a documentation pass on skill composition
- After a renaming or retirement to catch broken
Skill()references - During quarterly audits to spot orphaned skills
- When evaluating consolidation candidates (hubs are higher-risk to merge)
- When a new skill's outbound references should be sanity-checked
When NOT To Use
- For per-skill quality scoring, use
Skill(abstract:skills-eval)instead - For frontmatter/structure validation, use
Skill(abstract:plugin-review) - For hook-specific audits, use
Skill(abstract:hooks-eval)
Quick Start
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.
Core Outputs
| 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.
Dogfood Evidence
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.
Verification
Two ways to validate the audit output is trustworthy:
- Test-suite correctness check: Run
pytest -o addopts= plugins/abstract/tests/scripts/test_skill_graph.pyto 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. - Round-trip smoke check: Note the dangling-ref count from a 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.
Exit Criteria
- The graph builds:
skill_graph.pyruns againstplugins/without error and emits a node/edge count. - Dangling references are classified into bugs, external, and
placeholders (the three
Core Outputsrows resolve). - Every
Dangling: bugsentry is either fixed in the same session or filed as a tracked issue. -
pytest -o addopts= plugins/abstract/tests/scripts/test_skill_graph.pypasses. - The round-trip smoke check shows the dangling-ref count drops by at least the number of references fixed.
Related Skills
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 validation
References
- Implementation:
plugins/abstract/scripts/skill_graph.py - Tests:
plugins/abstract/tests/scripts/test_skill_graph.py - Composition documentation:
docs/quality-gates.md#skill-level-quality-gate-composition - Skill role taxonomy:
docs/skill-integration-guide.md#skill-role-taxonomy