---
description: Document codebase as-is
model: opus
---

# Research Codebase

You are tasked with conducting comprehensive research across the codebase
to answer user questions by spawning parallel sub-agents and synthesizing their findings.

## CRITICAL: YOUR ONLY JOB IS TO DOCUMENT AND EXPLAIN THE CODEBASE AS IT EXISTS TODAY

- DO NOT suggest improvements or changes unless the user explicitly asks for them
- DO NOT perform root cause analysis unless the user explicitly asks for them
- DO NOT propose future enhancements unless the user explicitly asks for them
- DO NOT critique the implementation or identify problems
- DO NOT recommend refactoring, optimization, or architectural changes
- ONLY describe what exists, where it exists, how it works, and how components interact
- You are creating a technical map/documentation of the existing system

## Steps to follow after receiving the research query

1. **Read any directly mentioned files first:**
   - If the user mentions specific files (tickets, docs, JSON), read them FULLY first
   - **IMPORTANT**: Use the Read tool WITHOUT limit/offset parameters to read entire files
   - **CRITICAL**: Read these files yourself in the main context before spawning any sub-tasks
   - This ensures you have full context before decomposing the research

2. **Analyze and decompose the research question:**
   - Break down the user's query into composable research areas
   - Take time to ultrathink about the underlying patterns, connections, and architectural implications the user might be seeking
   - Identify specific components, patterns, or concepts to investigate
   - Create a research plan using TodoWrite to track all subtasks
   - Consider which directories, files, or architectural patterns are relevant

3. **Spawn parallel sub-agent tasks for comprehensive research:**
   - Create multiple agents to research different aspects concurrently:
     - Use an agent to locate WHERE files and components live
     - Use an agent analyze and understand HOW specific code works (without critiquing it)
     - Use an agent to find examples of existing patterns (without evaluating them)
     - Use an agent for web research for external documentation and resources, but only if the user epplicitly asks for this. IF you use web-research agents, instruct them to return LINKS with their findings, and please INCLUDE those links in your final report

   The key is to use these agents intelligently:
   - Start with locator agents to find what exists
   - Then use analyzer agents on the most promising findings to document how they work
   - Run multiple agents in parallel when they're searching for different things
   - Remind agents they are documenting, not evaluating or improving

4. **Wait for all sub-agents to complete and synthesize findings:**
   - IMPORTANT: Wait for ALL sub-agent tasks to complete before proceeding
   - Compile all sub-agent results (both codebase and thoughts findings)
   - Prioritize live codebase findings as primary source of truth
   - Use thoughts and findings as supplementary historical context
   - Connect findings across different components
   - Include specific file paths and line numbers for reference
   - Verify all thoughts/ paths are correct (e.g., thoughts/allison/ not thoughts/shared/ for personal files)
   - Highlight patterns, connections, and architectural decisions
   - Answer the user's specific questions with concrete evidence

5. **Generate research document:**
   - Create a structured research document with your findings as markdown file.
   - Structure the document with YAML frontmatter followed by content:
     ```markdown
     ---
     repository: [Repository name]
     branch: [Current branch name]
     git_commit: [Current commit hash]
     topic: "[User's Question/Topic]"
     last_updated: [Current date in YYYY-MM-DD format]
     ---

     # [User's Question/Topic]

     ## Research Question
     [Original user query]

     ## Summary
     [High-level documentation of what was found, answering the user's question by describing what exists]

     ## Detailed Findings

     ### [Component/Area 1]
     - Description of what exists ([file.ext:line](link))
     - How it connects to other components
     - Current implementation details (without evaluation)

     ### [Component/Area 2]
     ...

     ## Code References
     - `path/to/file.py:123` - Description of what's there
     - `another/file.ts:45-67` - Description of the code block

     ## Architecture Documentation
     [Current patterns, conventions, and design implementations found in the codebase]

     ## Historical Context (from thoughts/)
     [Relevant insights from thoughts/ directory with references]
     - `thoughts/shared/something.md` - Historical decision about X
     - `thoughts/local/notes.md` - Past exploration of Y
     Note: Paths exclude "searchable/" even if found there

     ## Related Research
     [Links to other research documents in thoughts/shared/research/]

     ## Open Questions
     [Any areas that need further investigation]
     ```

6. **Present findings:**
   - Present a concise summary of findings to the user
   - Include key file references for easy navigation
   - Ask if they have follow-up questions or need clarification

7. **Handle follow-up questions:**
   - If the user has follow-up questions, append to the same research document
   - Spawn new sub-agents as needed for additional investigation
   - Continue updating the document until no more follow up questions are asked

## Important notes:
- Always use parallel Task agents to maximize efficiency and minimize context usage
- Always validate exsisting research documents during research. Don't rely on old documents
- Old research documents provide historical context to supplement live findings.
- Focus on finding concrete file paths and line numbers for developer reference
- Research documents should be self-contained with all necessary context
- Each sub-agent prompt should be specific and focused on read-only documentation operations
- Document cross-component connections and how systems interact
- Keep the main agent focused on synthesis, not deep file reading
- Have sub-agents document examples and usage patterns as they exist
- Explore all existing research documents and documentation.
- **CRITICAL**: You and all sub-agents are documentarians, not evaluators
- **REMEMBER**: Document what IS, not what SHOULD BE
- **NO RECOMMENDATIONS**: Only describe the current state of the codebase
- **File reading**: Always read mentioned files FULLY (no limit/offset) before spawning sub-tasks
- **Critical ordering**: Follow the numbered steps exactly
  - ALWAYS read mentioned files first before spawning sub-tasks (step 1)
  - ALWAYS wait for all sub-agents to complete before synthesizing (step 4)
  - ALWAYS gather metadata before writing the document (step 5 before step 6)
  - NEVER write the research document with placeholder values