What is the difference between a quick check and a deep dive?

A quick check takes under a minute for simple facts like version numbers, while a deep dive takes 5-15 minutes for complex decisions and saves findings to a Markdown file.

Can this skill help prevent broken code implementations?

Yes, it is specifically designed to trigger when it detects signs of API changes, security-critical tasks, or technologies that evolve rapidly.

How does the research skill find current information?

It uses a prioritized search strategy, first attempting to use MCP servers like Tavily or Exa for specialized results, falling back to built-in web search tools if needed.

Where are the research results stored?

Quick checks remain within the chat context for speed, while significant research is saved into a 'research/' folder in your repository for future team reference.

Web Research & API Verification

Name: Web Research & API Verification
Author: Light-Brands

byLight-Brands

Productivity & Workflow

Ensures code accuracy and avoids deprecated implementations by performing targeted real-time web research on APIs and libraries.

About

The Research skill empowers Claude to bridge the gap between its training data and the current state of the web by performing live verification of APIs, libraries, and security standards. It intelligently handles everything from sub-minute 'quick checks' for version numbers to comprehensive 15-minute 'deep dives' for complex architectural decisions, ensuring that your implementations are secure, modern, and bug-free. By prioritizing official documentation and changelogs, it provides a reliable source of truth that prevents hours of debugging caused by outdated knowledge.

Key Features

Automated tool selection favoring specialized MCP servers like Tavily and Exa
Actionable output formatting focusing on migration paths and code examples
Proactive identification of breaking changes and deprecated library methods
Persistent documentation of deep-dive findings in dedicated research directories
Tiered research modes for quick verification or in-depth architectural analysis
0 GitHub stars

Use Cases

Validating architectural patterns against the latest stable versions of frameworks like React or Next.js
Verifying the latest SDK methods and webhook payloads for services like Stripe or AWS
Resolving version-specific errors by checking recent GitHub releases and community discussions

About

Key Features

Automated tool selection favoring specialized MCP servers like Tavily and Exa
Actionable output formatting focusing on migration paths and code examples
Proactive identification of breaking changes and deprecated library methods
Persistent documentation of deep-dive findings in dedicated research directories
Tiered research modes for quick verification or in-depth architectural analysis
0 GitHub stars

Use Cases

Validating architectural patterns against the latest stable versions of frameworks like React or Next.js
Verifying the latest SDK methods and webhook payloads for services like Stripe or AWS
Resolving version-specific errors by checking recent GitHub releases and community discussions