github-deep-research

Automate multi-phase GitHub repository research and generate structured markdown reports.

Updated Jun 2, 2026

Search Tags:#github #report generation #data analysis #repository analysis #deep research

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill github-deep-research-bettercallfan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: github-deep-research
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/public/github-deep-research
Command: npx skills add https://github.com/bettercallfan/deerflow --skill github-deep-research-bettercallfan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, github-api, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates in-depth analysis of GitHub repositories, providing structured reports for comprehensive research.

Core Features & Use Cases

Multi-Round Research: Conducts a thorough, four-phase analysis using GitHub API, web searches, and web fetching.
Structured Reports: Generates markdown reports with executive summaries, timelines, metrics analysis, and diagrams.
Use Case: When needing a detailed analysis of a GitHub repository for competitive analysis, timeline reconstruction, or in-depth investigation.

Quick Start

Analyze the repository 'example-repo' using the 'github-deep-research' skill.

Frequently Asked Questions about github-deep-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate a structured analysis report for a GitHub repository?▼

You can automate GitHub repository research through a four-phase analysis that combines the GitHub API, web searches, and web fetching to generate structured markdown reports. This process yields executive summaries, timelines, metrics analysis, and diagrams for comprehensive investigation.

What is the best way to conduct competitive analysis using GitHub repository data?▼

Automating multi-round repository research is the best way to conduct competitive analysis using GitHub data. It combines the GitHub API with web fetching to extract repository metrics and reconstruct timelines, yielding a structured markdown report for in-depth investigation.

Can I reconstruct a project timeline by analyzing GitHub repository history?▼

Yes, you can reconstruct a project timeline by automating deep research on GitHub repositories. This performs multi-phase analysis using the GitHub API to extract metrics and events, generating a structured markdown report that details the project's timeline and evolution.

Does this GitHub repository analysis require an API key to access repository data?▼

Yes, GitHub repository analysis requires an API key because the multi-phase research process depends on the github-api and requests dependencies. You need these to authenticate, fetch repository data, and generate the final structured markdown analysis report.

What are the limitations of using automated tools for deep research on GitHub repositories?▼

Limitations of automated deep research on GitHub repositories include reliance on GitHub API rate limits and the accuracy of external web searches. The multi-phase analysis depends on fetching external data, meaning API access restrictions can impact the final structured markdown report.