Scan a directory or workspace for SKILL.md files across all agents and repos, capture supporting files (references, scripts, linked docs), dedupe vendored copies, enrich each Tessl tile with registry signals, and emit a canonical JSON inventory validated by JSON Schema. Then run four analytical phases in parallel against the inventory — staleness + git provenance (history, broken refs, contributors), quality (Tessl `skill review`), duplicates (similarity + LLM judgement), registry-search (per-standalone-skill registry suggestions, HTTP only) — and render a self-contained interactive HTML report with a top-of-report health overview, top-issues panel, recently-changed list, and per-tessl.json manifests view.
84
90%
Does it follow best practices?
Impact
97%
1.44xAverage score across 2 eval scenarios
Advisory
Suggest reviewing before use
Single consolidated discovery.json
100%
100%
Single consolidated report.html
100%
100%
Discovery includes repo-a
100%
100%
Discovery includes repo-b
100%
100%
Discovery EXCLUDES repo-c
100%
100%
Discovery script invoked once
0%
100%
Discovery command captured in summary
50%
100%
Both --repo flags present
0%
100%
stats.total_repos is 2
50%
100%
All four phase outputs at the consolidated path
100%
100%
Summary confirms repo-c excluded
100%
100%
discovery.json exists
100%
100%
discovery.json schema 1.3
0%
0%
discovery counts three skills
50%
100%
staleness.json produced
50%
100%
duplicates.json produced
100%
100%
quality.json produced or gracefully failed
100%
100%
report.html rendered
100%
100%
Bundled discovery script invoked
0%
100%
Phases dispatched in parallel
0%
100%
Render runs after all phases
100%
100%
Bundled render script used
0%
100%
Summary mentions correct counts
100%
100%
Graceful degradation surfaced
100%
100%