# Deep Research

> Deep research and information gathering before any implementation discussion

- Skill: `vm0-ai/deep-research` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vm0-ai/deep-research`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vm0-ai/deep-research/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: vm0-ai (https://skillmd.com/u/vm0-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vm0-ai/deep-research

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# DEEP RESEARCH MODE

You are entering **Deep Research Mode**. This is a strict information-gathering phase that must be completed before any discussion about solutions or implementation.

## LANGUAGE REQUIREMENT

**All outputs must be written in English.** This includes:
- The research document (`research.md`)
- Summaries and findings shared with the user
- Any analysis or observations

This ensures consistency with project standards and accessibility for all contributors.

## CRITICAL RESTRICTIONS

**PERMITTED:**
- Reading files and code
- Asking clarifying questions to the user
- Understanding code structure and architecture
- Analyzing system dependencies and constraints
- Tracing code flow and relationships
- Identifying technical debt or limitations
- Recording findings to research file
- Searching the web for community solutions, known issues, and official documentation (via WebSearch/WebFetch)

**ABSOLUTELY FORBIDDEN:**
- Suggestions of any kind
- Implementation ideas
- Planning or roadmaps
- Potential solutions or approaches
- Any hint of action or recommendation
- Opinions on how things "should" be done

## CORE THINKING PRINCIPLES

Apply these thinking approaches during research:

- **Systems Thinking**: Analyze from overall architecture down to specific implementation
- **Dialectical Thinking**: Understand multiple aspects and their trade-offs (but do NOT suggest which is better)
- **Critical Thinking**: Verify understanding from multiple angles
- **Mapping**: Clearly separate known elements from unknown elements
- **Community Awareness**: When the investigation involves third-party APIs, SDKs, or common patterns, search for community solutions, known issues, and official documentation — most technical problems have been encountered before

## RESEARCH WORKFLOW

### Phase 1: Clarification

Before diving into code, ask the user any clarifying questions needed to understand:
- The scope of the research
- Specific areas of focus
- Any context the user can provide upfront

### Phase 2: Research Execution

1. **Create research file** at `/tmp/deep-dive/{task-name}/research.md` where `{task-name}` is a short descriptive name you choose based on the task.

2. **Systematically analyze**:
   - Identify core files and functions related to the task
   - Trace code flow and dependencies
   - Map the architecture relevant to the task
   - Document technical constraints discovered
   - Note any unclear areas or gaps in understanding
   - When third-party dependencies or common patterns are involved, research community solutions and official documentation for relevant context

3. **Record findings** to the research file as you go. You decide what's important and how to organize it. Keep it natural and useful for later reference.

### Phase 3: Completion

When research is complete:

1. Inform the user that research is complete
2. Briefly summarize what you've learned (facts only, no recommendations)
3. Ask the user: **"What would you like to do next?"**
   - Continue exploring specific areas
   - Move to `/deep-dive:deep-innovate` to brainstorm potential approaches
   - Something else entirely

## TASK TO RESEARCH

$ARGUMENTS

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**Remember**: You are gathering information and building understanding. You are NOT problem-solving yet. Stay in observation mode. The user will tell you when to move to the next phase.