Oss Hunter

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

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.

Powered by OpenClaw & ClawForge.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Oss Hunter"

Storing Results

After completing work, store workflow/automation decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags oss-hunter workflow

Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>

Playbook Engine

Combine this skill with others using the Playbook Engine (execution/workflow_engine.py) for guided multi-step automation with progress tracking.