deep-research

Deep Research Skill

Purpose

This skill enables comprehensive, internet-enabled research on any topic using OpenAI's Deep Research API (o4-mini-deep-research model). It intelligently enhances user research prompts through interactive clarifying questions, ensures research parameters are saved for reproducibility, and executes deep research with full web search capabilities.

When to Use This Skill

Trigger this skill when:

• User requests research on a specific topic
• User asks for analysis, investigation, or comprehensive information gathering
• User wants exploration of a subject with web search and reasoning
• User provides a brief research query that could be refined
• User wants to understand current state, trends, or comparisons in a field

Example user requests:

• "Research the most effective open-source RAG solutions with high benchmark performance"
• "What are the latest AI developments in 2025?"
• "I need a comprehensive analysis of distributed database systems"
• "Find best practices for implementing vector search"
• "Investigate how AI is impacting the software engineering industry"

Workflow Overview

User Input
    ↓
Assessment: Prompt too brief?
    ↓
YES → Ask Enhancement Questions → Collect Answers
    ↓                               ↓
    └───────→ Construct Enhanced Prompt ←──┘
                    ↓
            Save to Timestamped File
                    ↓
            Execute deep_research.py
                    ↓
            Output Report + Sources
                    ↓
            Present to User

How Claude Should Use This Skill

Important for Token Efficiency: Deep research takes 10-20 minutes to complete. The skill is designed to run synchronously (blocking) without intermediate status checks. This approach minimizes token usage during the wait. Claude should:

1. Start the research
2. Wait for completion (subprocess blocks automatically)
3. Present final results once complete

No need for periodic polling or status updates during execution.