Which sources does the skill use for research?

It primarily uses GitHub via Octocode MCP and library documentation via Context7 MCP, with WebFetch as a final fallback if specialized tools are unavailable.

Can this skill search my local files?

No, this skill is strictly for external research. Local codebase searches are handled by standard tools like Grep, Glob, and Read.

Why is research conducted before the planning phase?

Researching first informs the planning agent, ensuring the AI chooses the correct architectural patterns and avoids deprecated practices before any code is written.

What is the Iron Law of this skill?

The Iron Law mandates that external research should only occur when there is a clear AI knowledge gap or an explicit user request, preventing unnecessary latency and token usage.

GitHub Research & External Docs

Name: GitHub Research & External Docs
Author: romiluz13

byromiluz13

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学習とドキュメンテーション

Conducts deep external research across GitHub repositories and official library documentation to bridge AI knowledge gaps for modern technologies.

概要

This skill empowers Claude to proactively investigate external code patterns, best practices, and API documentation from GitHub and specialized library indexes. By utilizing tools like Octocode and Context7, it ensures that implementation plans are grounded in real-world examples and the latest releases, particularly for technologies emerging after the AI's training cutoff. It prioritizes efficiency by researching only when necessary and providing structured summaries that inform planning and debugging phases without cluttering the local workspace.

主な機能

38 GitHub stars
Automated GitHub repository and code structure analysis via Octocode MCP
Direct querying of official library documentation through Context7 MCP
Structured research summaries designed for seamless integration with AI planning agents
Smart research triggers for post-2024 technologies and complex integrations
Tiered fallback system ensuring data retrieval even when primary tools are unavailable

ユースケース

Investigating unfamiliar API implementation patterns for libraries released after the AI training cutoff
Identifying best practices and real-world examples in open-source repositories before starting a complex integration
Resolving persistent external service errors by searching for known community issues and fixes on GitHub

概要

主な機能

38 GitHub stars
Automated GitHub repository and code structure analysis via Octocode MCP
Direct querying of official library documentation through Context7 MCP
Structured research summaries designed for seamless integration with AI planning agents
Smart research triggers for post-2024 technologies and complex integrations
Tiered fallback system ensuring data retrieval even when primary tools are unavailable

ユースケース

Investigating unfamiliar API implementation patterns for libraries released after the AI training cutoff
Identifying best practices and real-world examples in open-source repositories before starting a complex integration
Resolving persistent external service errors by searching for known community issues and fixes on GitHub