When should I escalate to the knowledge-builder command?

You should escalate when the topic is foundational to your entire project and requires comprehensive, multi-file documentation and Socratic exploration rather than a quick 5-minute overview.

How does the research skill differ from standard AI search?

The research skill follows a structured technical synthesis process designed specifically for developers, providing mental models, code patterns, and tiered source verification rather than just a general summary.

Can it save research findings to my project?

Yes, the skill can use the Write tool to save research summaries into a 'Research/' directory within your project for future reference.

What sources does the skill prioritize?

It uses a Tier 1 authority system, prioritizing official documentation, academic papers, and core maintainer blogs over general community forums.

Technical Topic Researcher

Name: Technical Topic Researcher
Author: rysweet

byrysweet

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Learning & Documentation

Conducts rapid web research and synthesizes technical information to help developers master unfamiliar technologies and concepts.

About

This skill empowers Claude to perform high-speed research into new libraries, frameworks, or debugging issues by fetching current data from authoritative sources. It structures findings into actionable technical summaries, providing clear mental models, best practices, and common pitfalls directly within your workflow. Whether you're exploring a new API or troubleshooting a cryptic 'ECONNREFUSED' error, this skill bridges the gap between searching and implementing by providing context-aware, synthesized intelligence.

Key Features

Multi-tier source prioritization focusing on official documentation and core maintainer blogs
Context-aware debugging research to resolve specific error messages and environment issues
Standardized technical reports including mental models, use cases, and common gotchas
16 GitHub stars
Intelligent escalation to deep-dive tools for complex architectural decision-making
Automated web searching and content synthesis from authoritative technical sources

Use Cases

Quickly learning the core concepts and best practices of a new framework or library
Diagnosing cryptic terminal errors by researching common community-verified fixes
Performing architectural tradeoff analysis between competing technologies like REST and GraphQL

About

Key Features

Multi-tier source prioritization focusing on official documentation and core maintainer blogs
Context-aware debugging research to resolve specific error messages and environment issues
Standardized technical reports including mental models, use cases, and common gotchas
16 GitHub stars
Intelligent escalation to deep-dive tools for complex architectural decision-making
Automated web searching and content synthesis from authoritative technical sources

Use Cases

Quickly learning the core concepts and best practices of a new framework or library
Diagnosing cryptic terminal errors by researching common community-verified fixes
Performing architectural tradeoff analysis between competing technologies like REST and GraphQL