Skill: sliverp/repo-scout (version 1.0.0)

--- name: repo-scout description: "Discover, evaluate, and rank GitHub repositories in any ecosystem or domain. Produces a structured ranking document with star counts, languages, issue health, and contribution friendliness scores. Use when scouting for open-source projects to contribute to, evaluating technology options, doing competitive analysis, or exploring a new ecosystem." --- # Repo Scout — Repository Discovery & Ranking ## Overview Systematically discover and rank GitHub repositories in a given ecosystem. Produces a structured, actionable ranking document. **Use cases**: Open-source contribution targeting, technology landscape surveys, competitive analysis, ecosystem exploration. ## Prerequisites Before starting, the user must have GitHub CLI authenticated: ```bash gh auth status # Must show "Logged in" ``` If not configured, ask the user to provide: 1. **GitHub username** — for searching and attribution 2. **GitHub token** — run `gh auth login` or set `export GH_TOKEN=<token>` Without auth, `gh` API calls will hit rate limits quickly and private repo data won't be accessible. ## Workflow ### Step 1: Define Scope Ask the user for (with sensible defaults): | Parameter | Default | Example | |-----------|---------|---------| | Ecosystem keyword(s) | *(required)* | "AI agent", "LLM tools", "Kubernetes" | | Target count | 15 | top 15 by stars | | Minimum stars | 5,000 | Filter out small repos | | Language filter | *(any)* | Python, TypeScript | | Additional criteria | *(none)* | "must have bug label issues" | ### Step 2: Search & Collect Use multiple search strategies to find candidates: ``` Search strategies: 1. GitHub search: "{keyword}" sorted by stars 2. "awesome-{keyword}" curated lists 3. GitHub trending in the domain 4. Web search for "{keyword} top open-source projects {year}" ``` For each candidate repository, collect: | Data Point | How to Get | |------------|-----------| | Star count | GitHub API / web | | Primary language | GitHub API | | Last commit date | GitHub API | | Open issue count | GitHub API | | Bug-labeled issues | `gh issue list --label bug --state open --limit 5` | | `good first issue` count | GitHub search | | CONTRIBUTING.md exists? | Check repo root | | CI configured? | Check `.github/workflows/` | | PR template exists? | Check `.github/PULL_REQUEST_TEMPLATE.md` | | License | GitHub API | ### Step 3: Score & Rank Score each repository on a **contribution friendliness** scale: | Factor | Weight | Scoring | |--------|--------|---------| | Actionable bug issues | 30% | 3=many clear bugs, 1=none | | Activity (recent commits) | 20% | 3=daily, 2=weekly, 1=monthly+ | | Contribution docs | 15% | 3=CONTRIBUTING+template, 2=partial, 1=none | | CI/CD health | 15% | 3=green CI, 2=partial, 1=none | | Community size (stars) | 10% | 3=>50K, 2=>10K, 1=>5K | | Response time to PRs | 10% | 3=<3d, 2=<7d, 1=>7d | ### Step 4: Filter Out Mark repositories to **skip** if: - Non-code repo (awesome-lists, documentation-only, resource collections) - Desktop/mobile UI bugs requiring hardware access - No actionable bug issues (only feature requests or stale issues) - Archived or unmaintained (no commits in 6+ months) - Hostile contribution environment (PRs routinely ignored) ### Step 5: Produce Ranking Document Write `{workspace}/ecosystem-top{N}.md`: ```markdown # {Ecosystem} — Top {N} Repositories > Generated: {date} > Keywords: {keywords} > Minimum stars: {min_stars} ## Rankings | Rank | Repository | Stars | Language | Open Bugs | Score | Notes | |------|-----------|-------|----------|-----------|-------|-------| | 1 | owner/repo | 45.2K | Python | 12 | 8.5/10 | Active, good docs | | 2 | ... | ... | ... | ... | ... | ... | ## Skipped Repositories | Repository | Reason | |-----------|--------| | owner/repo | Non-code (awesome-list) | ## Detailed Profiles ### 1. owner/repo (45.2K ⭐) - **Language**: Python - **Last commit**: 2 days ago - **Open issues**: 234 (12 labeled `bug`) - **CONTRIBUTING.md**: ✅ - **CI**: ✅ GitHub Actions - **Score breakdown**: Activity 3/3, Bugs 3/3, Docs 2/3, CI 3/3, Community 2/3, Response 2/3 - **Notes**: Very active, welcoming community ``` ## Output - `{workspace}/ecosystem-top{N}.md` — Structured ranking document ready for downstream use ## Tips - When used as part of a contribution campaign, the output feeds directly into the **issue-hunter** skill for issue analysis. - For technology evaluation, the ranking + detailed profiles are the final deliverable. - Re-run periodically to catch ecosystem changes.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)