oss-hunter
Automatically hunt for high-impact OSS contribution opportunities in trending repositories.
Best use case
oss-hunter is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automatically hunt for high-impact OSS contribution opportunities in trending repositories.
Teams using oss-hunter should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/oss-hunter/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How oss-hunter Compares
| Feature / Agent | oss-hunter | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Automatically hunt for high-impact OSS contribution opportunities in trending repositories.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# OSS Hunter 🎯 A precision skill for agents to find, analyze, and strategize for high-impact Open Source contributions. This skill helps you become a top-tier contributor by identifying the most "mergeable" and influential issues in trending repositories. ## When to Use - Use when the user asks to find open source issues to work on. - Use when searching for "help wanted" or "good first issue" tasks in specific domains like AI or Web3. - Use to generate a "Contribution Dossier" with ready-to-execute strategies for trending projects. ## Quick Start Ask your agent: - "Find me some help-wanted issues in trending AI repositories." - "Hunt for bug fixes in langchain-ai/langchain that are suitable for a quick PR." - "Generate a contribution dossier for the most recent trending projects on GitHub." ## Workflow When hunting for contributions, the agent follows this multi-stage protocol: ### Phase 1: Repository Discovery Use `web_search` or `gh api` to find trending repositories. Focus on: - Stars > 1000 - Recent activity (pushed within 24 hours) - Relevant topics (AI, Agentic, Web3, Tooling) ### Phase 2: Issue Extraction Search for specific labels: - `help-wanted` - `good-first-issue` - `bug` - `v1` / `roadmap` ```bash gh issue list --repo owner/repo --label "help wanted" --limit 10 ``` ### Phase 3: Feasibility Analysis Analyze the issue: 1. **Reproducibility**: Is there a code snippet to reproduce the bug? 2. **Impact**: How many users does this affect? 3. **Mergeability**: Check recent PR history. Does the maintainer merge community PRs quickly? 4. **Complexity**: Can this be solved by an agent with the current tools? ### Phase 4: The Dossier Generate a structured report for the human: - **Project Name & Stars** - **Issue Link & Description** - **Root Cause Analysis** (based on code inspection) - **Proposed Fix Strategy** - **Confidence Score** (1-10) ## Limitations - Accuracy depends on the availability of `gh` CLI or `web_search` tools. - Analysis is limited by context window when reading very large repositories. - Cannot guarantee PR acceptance (maintainer discretion). --- ## Contributing to the Matrix Build a better hunter by adding new heuristics to Phase 3. Submit your improvements to the [ClawForge](https://github.com/jackjin1997/ClawForge). *Powered by OpenClaw & ClawForge.*
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