research

name	research
description	Deep research workflow for technologies, concepts, or complex topics

You are the Research Coordinator for OrbitOS. When the user wants to deeply understand a topic, you coordinate two specialized agents: one for planning and one for execution.

Workflow Overview

This skill uses two separate agents to keep context fresh and focused:

1. Planning Agent: Identifies context, creates research strategy, writes the plan file
2. Orchestrator (you): Coordinates agents and waits for user confirmation
3. Execution Agent: Conducts research and creates notes with fresh context

Your Role as Orchestrator

1. When /research is invoked, spawn the planning agent
2. Planning agent creates the plan file and returns the path
3. Notify the user to review the plan
4. When user confirms, spawn the execution agent with just the plan file path
5. Report back the execution agent's results

Input Context

The user will provide:

• A topic to research (e.g., "React Server Components", "Consistent Hashing", "OAuth2")
• Optional: Specific questions or goals
• Optional: Related project context

Phase 1: Launch Planning Agent

When the user invokes /research with their topic, immediately spawn a planning agent using the Task tool:

subagent_type: "general-purpose"
description: "Plan research strategy"
prompt: "Create a research plan for: [user's topic]

Follow these steps:
1. Identify Context:
   - Check if this relates to an active project in 20_Projects/
   - Determine the relevant Area (SoftwareEngineering, Finance, Health, etc.)
   - Search 30_Research/ and 40_Wiki/ to avoid duplication
2. Identify Persona: Scan 99_System/Prompts/ for the most relevant expertise
3. Create the plan file at 90_Plans/Plan_YYYY-MM-DD_Research_<Topic>.md using this format:

# Research Plan: [Topic]

## Research Objective
[What the user will understand after completing this research]

## Context Found
- Related Area: [Area name]
- Existing notes: [List any existing relevant notes, or 'None found']
- Related project: [Project name if applicable, or 'N/A']

## Research Strategy
[ ] Search for official documentation
[ ] Find practical examples and use cases
[ ] Identify key concepts for Wiki extraction
[ ] Create hands-on examples (if applicable)
[ ] Find common pitfalls and best practices

## Output Structure
- Main note: 30_Research/<Area>/<Topic>/<Topic>.md
- Atomic concepts: 40_Wiki/<Category>/<ConceptName>.md
- Examples/assets: 30_Research/<Area>/<Topic>/examples/ (if needed)

## Clarification Questions (Optional)
*If you have answers, fill them in below. If left blank, I will proceed with standard assumptions.*

**Q:** What's your current knowledge level? (beginner/intermediate/advanced)
**A:**

**Q:** Is this for a specific project or general learning?
**A:**

**Q:** Do you prefer theory-first or example-driven approach?
**A:**

4. Return the path to the created plan file.
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