A professional scouting tool that scans GitHub to identify potential AI company customers based on repository activity and technical signals.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pans-github-scout
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install pans-github-scout using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is pans-github-scout?
pans-github-scout is a technical lead generation tool specifically designed to find companies deeply involved in the artificial intelligence and machine learning landscape. By scanning GitHub for specific markers—such as large model projects, training code, and specialized ML repositories—it allows teams to identify prospects with high compute needs or innovative engineering teams. As a core component of your Openclaw Skills library, this tool bridges the gap between technical repository data and actionable business development leads.
pans-github-scout Use Cases
- Identifying high-growth AI startups for investment or acquisition research.
- Generating sales leads for GPU providers and cloud infrastructure services.
- Monitoring the adoption of specific large language model (LLM) frameworks.
- Automating competitive analysis by tracking repository growth and developer activity.
How pans-github-scout Works
- The user defines search dimensions such as keyword-based ML repositories or specific LLM training scripts.
- The tool queries GitHub's API to find repositories matching these technical parameters.
- Results are passed through a filtering layer that checks for star counts, recent commit activity, and organizational metadata.
- The system identifies organization-level leads by analyzing the project owners and contributors.
- Qualified leads are formatted and prepared for bulk export into standard data formats.
pans-github-scout Setup
To use this tool effectively within the Openclaw Skills environment, ensure you have Python 3.8+ and the requests library installed.
# Install the necessary dependency
pip install requests
# Perform a search for machine learning repositories with over 100 stars
python3 scripts/scout.py --search "machine learning" --min-stars 100
# Filter and find active projects with high engagement
python3 scripts/scout.py --filter --min-stars 500 --updated-within 30
# Export the discovered leads to a CSV file for CRM integration
python3 scripts/scout.py --export leads.csv
pans-github-scout Data Schema & Taxonomy
| Category | Details |
|---|---|
| Search Parameters | AI/ML repositories, LLM projects, training code structures |
| Filtering Metrics | Star count, update frequency, repository activity levels, company size |
| Supported Formats | CSV, JSON |
| Output Fields | Repository name, organization metadata, star count, last updated timestamp |
pans-github-scout Advanced Features
- Intelligent filtering based on compute demand signals found within training code.
- Multi-format export options (CSV/JSON) for seamless integration with CRM platforms.
- Targeted discovery of large model projects and niche AI engineering teams.
- Optimized search queries compatible with the Openclaw Skills framework for automated lead scouting.
SKILL.md
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