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deep-research

Deep research and information gathering before any implementation discussion

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Dépôt
okou-ai/team-skills
Dernière activité de la source
14 avril 2026 à 04:55
Langue détectée de SKILL.md
anglais
Étoiles
1
Forks
2

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SKILL.md
Instructions source · Aperçu en lecture seule
name
deep-research
description
Deep research and information gathering before any implementation discussion
# 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 --- **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.
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