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GitHub

github-research

Ingest deep-research outputs to discover and prioritize GitHub repositories.

Updated Apr 23, 2026
Search Tags:#automation#research#github#blueprint#code-analysis#repositories
One-click install
npx skills add https://github.com/Embers-of-the-Fire/agent-research-skills-opencode --skill github-research-embers-of-the-fire
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: github-research
Source: https://github.com/Embers-of-the-Fire/agent-research-skills-opencode/tree/main/.opencode/skills/github-research
Command: npx skills add https://github.com/Embers-of-the-Fire/agent-research-skills-opencode --skill github-research-embers-of-the-fire

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill automates end-to-end GitHub research by ingesting deep-research outputs, discovering relevant repositories from multiple sources, and preparing for deep analysis and reuse.

Core Features & Use Cases

  • Discover and prioritize GitHub repositories related to a research topic using deep-research outputs and multi-source signals.
  • Deep-dive analysis: fetch or clone code, map architectures and dependencies, and produce reusable integration blueprints.
  • Generate structured artifacts (repo_db-like records, phase outputs) for downstream blueprint and tooling.

Quick Start

Run /github-research with a path to your deep-research outputs directory to generate a prioritized repo set and blueprint.

Frequently Asked Questions about github-research

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

FAQPage Schema
How do I automate GitHub repository research from deep-research outputs?▼

To automate GitHub repository research, you can ingest deep-research outputs to discover relevant repositories from multiple sources, apply screening, and perform deep code analysis to prepare a structured integration blueprint.

What's the best way to generate an integration blueprint from discovered GitHub repositories?▼

Generating an integration blueprint involves fetching or cloning the discovered GitHub repositories, mapping their architectures and dependencies, and producing reusable phase artifacts for subsequent downstream phases.

Can I use deep code analysis to map repository architectures and dependencies automatically?▼

Yes, deep code analysis automatically fetches or clones code to map repository architectures and dependencies, transforming raw repository data into a structured database and reusable integration blueprints.

How do I screen and prioritize GitHub repositories related to a specific research topic?▼

You can screen and prioritize GitHub repositories by ingesting deep-research outputs and leveraging multi-source signals to evaluate relevance, generating a structured repository-database for your research topic.

Does the GitHub research workflow require prior deep-research outputs to start?▼

Yes, the GitHub research workflow requires a path to your deep-research outputs directory to start, using those prior signals to discover, screen, and analyze relevant repositories for integration.

What structured artifacts are generated after analyzing GitHub repositories for reuse?▼

Analyzing GitHub repositories generates structured artifacts including repo_db-like records and phase outputs, which prepare the integration blueprint and enable subsequent reuse in downstream tooling.

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