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Audit Skill() refs; detect hubs, isolates, and dangling targets.
Passed 19 of 22 test cases with the skill, and 7 of 22 without it.
and 11 more in the full report
14 fixed8 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I need to quickly inspect the top 10 skill hubs and orchestrators in the `plugins` directory from my terminal. What exact command should I run?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies running `python3 plugins/abstract/scripts/skill_graph.py --plugins-root plugins --top-n 10`. | Missed | Passed |
The instructions your model reads when the skill loads.
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
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.