find-awesome-skill

name	find-awesome-skill
description	Use this skill when looking for curated skill recommendations from awesome lists, with exact install commands.
metadata	{"internal":true}

Find Awesome Skill

Search the user's configured awesome skill sources, merge duplicates, and return concise recommendations with install commands.

Source discovery

Awesome sources are loaded from these layers, in this order:

1. .agents/awesome-skill-sources.local.json
2. .agents/awesome-skill-sources.json
3. ~/.agents/awesome-skill-sources.json
4. The current repo's own awesome-skills.json as the default source unless explicitly disabled

Duplicate sources are deduped by repo + path.

Use this section when the user asks which sources are searched, or when the CLI returns no results and you need to diagnose missing configuration.

Search flow

1. Primary path — use the CLI

Run the bundled finder with JSON output (machine contract):

npx cyber-skills@<version> awesome find "<query>" --json

Parse the JSON array and present concise results with install commands. Default CLI output (without --json) is human-readable prose for summaries only.

2. Fallback — when the CLI cannot fully answer

Use manual reasoning from the source layers above when:

• cyber-skills is unavailable or awesome find fails
• the query returns zero results — inspect configured sources and suggest configure-awesome-sources
• the user asks which sources are searched (see Source discovery)
• you need to explain match rationale beyond JSON fields (corroboration across sources, tag vs summary nuance)

When falling back, merge duplicate repo or skill entries across sources and rank by:

• exact name match
• summary match
• tag match
• corroboration count
• source class preference

Return concise results with:

• repo or repo+skill identity
• why it matched
• primary why_recommended
• whether other sources also recommended it
• exact npx skills add ... install command

Guidance

• Exact name matches should be treated as the strongest signal.
• Tag and summary matches matter next.
• Corroboration across multiple awesome sources should increase confidence but should not hide why a result matched.
• If no results match, say so directly and suggest adding or configuring more awesome sources.