OSS Hunter 🎯

Quick Start

• "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

Phase 1: Repository Discovery

web_search

gh api

• Stars > 1000
• Recent activity (pushed within 24 hours)
• Relevant topics (AI, Agentic, Web3, Tooling)

Phase 2: Issue Extraction

• help wanted

• good first issue

• bug

• v1

  /

  roadmap

gh issue list --repo owner/repo --label "help wanted" --limit 10

Phase 3: Feasibility Analysis

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

• Project Name & Stars
• Issue Link & Description
• Root Cause Analysis (based on code inspection)
• Proposed Fix Strategy
• Confidence Score (1-10)

Example Dossier

🦜 LangChain #35009

Status: Potential Fix Identified Description: ToolMessageChunk merges None content into "NoneNone". Strategy: Modify

coerce_args

in

tool.py

to skip coercion for

NoneType

. Confidence: 9/10 (Reproducible locally).

Contributing to the Matrix