oss-issue-scout

Analyze a user-provided Git repository and GitHub issues to confirm contribution rules (CONTRIBUTING, CLA/DCO, templates) and shortlist high-value, maintainer-friendly issues likely to be accepted. Use when a user wants help selecting open-source issues to contribute to, or when triaging a GitHub repo for good first contributions.

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Install skill "oss-issue-scout" with this command: npx skills add peterfile/my-common-skills/peterfile-my-common-skills-oss-issue-scout

OSS Issue Scout

Overview

Identify contribution rules and surface a small set of high-value, maintainer-friendly issues for a given GitHub repository.

Workflow

1) Confirm inputs

  • Ask for the repo URL or a local repo path and whether GitHub access is available.
  • Ask for constraints: language/stack familiarity, time budget, desired impact, preferred work type (bug/doc/test/feature), and skill level.
  • Ask if the user can run tests and open PRs.

2) Read contribution rules and signals

  • Check repo docs locally or via GitHub: CONTRIBUTING.md, README, CODE_OF_CONDUCT, SECURITY.md, LICENSE, GOVERNANCE, MAINTAINERS, issue/PR templates, .github/ folder, CI configs.
  • Note CLA/DCO requirements, branch naming, commit rules, test expectations, and required checks.
  • If any open-source or GitHub practice is unclear, use Context7 to refresh before advising.

3) Pull issues via GitHub MCP

  • Discover available GitHub MCP resources/templates and use them to list open issues with labels, assignees, milestones, and last activity.
  • Prefer issues labeled good first issue/help wanted/bug/docs/tests and those with clear acceptance criteria.
  • Filter out: stale/needs info, blocked, huge refactors, security-sensitive items, no reproduction steps, or already assigned issues.
  • Cross-check for linked PRs, duplicates, or active discussions that indicate ongoing work.

4) Score and shortlist

  • Use references/issue-scoring.md to score value, acceptance likelihood, clarity, and effort fit.
  • Select 3-7 issues with the best balance of impact and low acceptance risk; keep scope aligned to user constraints.

5) Report back

  • Provide a concise list of recommended issues with links, labels, last activity, estimated effort, and why they are good picks.
  • Summarize contribution rules and any blockers.
  • Ask targeted questions if key info is missing or if all candidate issues are low quality.

Output format

  • Recommended issues
  • Contribution rules and constraints
  • Risks/unknowns
  • Questions for the user
  • Suggested next actions

References

  • Read references/issue-scoring.md when scoring or filtering issues.

Source Transparency

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