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OSS Hunter 🎯

oss-hunter

Automatically hunt for high-impact OSS contribution opportunities in trending repositories.

techwavedev/agi-agent-kit0installs4stars

SKILL.md

Full skill instructions

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-INTEGRATION-START -->

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.

<!-- AGI-INTEGRATION-END -->