run-research

Conduct structured technical research on coding bugs and API behaviors.

11|Updated Mar 8, 2026

Search Tags:#debugging #decision making #research #problem solving #information gathering #technical investigation

Ready to run

npx skills add https://github.com/yigitkonur/skills-by-yigitkonur --skill run-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: run-research
Source: https://github.com/yigitkonur/skills-by-yigitkonur/tree/main/skills/run-research
Command: npx skills add https://github.com/yigitkonur/skills-by-yigitkonur --skill run-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill tackles complex technical questions by performing disciplined, multi-source research, preventing shallow conclusions from single snippets or AI outputs.

Core Features & Use Cases

Systematic Investigation: Guides you through a structured workflow for debugging, library selection, architecture trade-offs, and API behavior research.
Multi-Source Validation: Integrates web search, Reddit discussions, and deep AI analysis to ensure findings are robust.
Use Case: You're debugging a cryptic runtime error. Use this Skill to systematically search Google for error messages, validate potential fixes on Stack Overflow and Reddit, and use deep research to analyze your specific code context if needed.

Quick Start

Use the run-research skill to investigate the error message "unhandled promise rejection" in your Node.js application.

Frequently Asked Questions about run-research

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

FAQPage Schema

How do I conduct technical investigation for a cryptic coding bug?▼

To investigate a coding bug, you need a structured workflow that integrates web search, Reddit validation, and deep AI analysis to systematically find and verify potential fixes. This multi-source approach prevents shallow conclusions from single snippets.

What is the best way to research architecture trade-offs and library choices?▼

The best way to research architecture trade-offs and library choices is through multi-source validation. By combining web search results with community discussions on Reddit and deep AI analysis, you ensure your findings are comprehensive and reliable.

Can I use deep research to analyze API behaviors and my specific code context?▼

Yes, deep research can analyze API behaviors and your specific code context. By using specific activation boundaries and core operating rules, the research ensures robust and reliable findings directly relevant to your codebase.

Why does relying on a single AI output or code snippet fail for complex technical problems?▼

Relying on a single AI output or code snippet fails because it often leads to shallow conclusions. Complex technical problems require disciplined, multi-source research across web searches and community validation to ensure robust and reliable findings.

When do I need a structured workflow for technical investigation?▼

You need a structured workflow for technical investigation when debugging cryptic runtime errors, evaluating library choices, or analyzing architecture trade-offs. It guides you through systematic information gathering to prevent unreliable conclusions.