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---
description: Document codebase as-is without evaluation or recommendations
---
# 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
## Initial Setup:
When this command is invoked, respond with:
```
I'm ready to research the codebase. Please provide your research question or area of interest, and I'll analyze it thoroughly by exploring relevant components and connections.
```
Then wait for the user's research query.
## 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 Task agents to research different aspects concurrently
- We now have specialized agents that know how to do specific research tasks:
**For codebase research:**
- Use the **codebase-locator** agent to find WHERE files and components live
- Use the **codebase-analyzer** agent to understand HOW specific code works (without critiquing it)
- Use the **codebase-pattern-finder** agent to find examples of existing patterns (without evaluating them)
**IMPORTANT**: All agents are documentarians, not critics. They will describe what exists without suggesting improvements or identifying issues.
**For web research (only if user explicitly asks):**
- Use the **web-search-researcher** agent for external documentation and resources
- IF you use web-research agents, instruct them to return LINKS with their findings, and please INCLUDE those links in your final report
**For GitHub tickets (if relevant):**
- Use the **GitHub cli** agent to get full details of a specific ticket
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
- Each agent knows its job - just tell it what you're looking for
- Don't write detailed prompts about HOW to search - the agents already know
- 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
- Prioritize live codebase findings as primary source of truth
- Connect findings across different components
- Include specific file paths and line numbers for reference
- Highlight patterns, connections, and architectural decisions
- Answer the user's specific questions with concrete evidence
5. **Gather metadata for the research document:**
- Run Bash() tools to generate all relevant metadata
- Filename: `docs/claude/research/YYYY-MM-DD-XXXX-description.md`
- Format: `YYYY-MM-DD-XXXX-description.md` where:
- YYYY-MM-DD is today's date
- XXXX is the ticket number (omit if no ticket)
- description is a brief kebab-case description of the research topic
- Examples:
- With ticket: `2025-01-08-1478-parent-child-tracking.md`
- Without ticket: `2025-01-08-authentication-flow.md`
6. **Generate research document:**
- Use the metadata gathered in step 4
- Structure the document with YAML frontmatter followed by content:
```markdown
---
date: [Current date and time with timezone in ISO format]
researcher: [Researcher name from metadata]
git_commit: [Current commit hash]
branch: [Current branch name]
topic: "[User's Question/Topic]"
tags: [research, codebase, relevant-component-names]
status: complete
last_updated: [Current date in YYYY-MM-DD format]
last_updated_by: [Researcher name]
---
# Research: [User's Question/Topic]
**Date**: [Current date and time with timezone from step 4]
**Researcher**: [Researcher name from metadata]
**Git Commit**: [Current commit hash from step 4]
**Branch**: [Current branch name from step 4]
## 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]
## Related Research
[Links to other research documents in docs/claude/research/]
## Open Questions
[Any areas that need further investigation]
```
7. **Add GitHub permalinks (if applicable):**
- Check if on main branch or if commit is pushed: `git branch --show-current` and `git status`
- If on main/master or pushed, generate GitHub permalinks:
- Get repo info: `gh repo view --json owner,name`
- Create permalinks: `https://github.com/{owner}/{repo}/blob/{commit}/{file}#L{line}`
- Replace local file references with permalinks in the document
8. **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
9. **Handle follow-up questions:**
- If the user has follow-up questions, append to the same research document
- Update the frontmatter fields `last_updated` and `last_updated_by` to reflect the update
- Add `last_updated_note: "Added follow-up research for [brief description]"` to frontmatter
- Add a new section: `## Follow-up Research [timestamp]`
- Spawn new sub-agents as needed for additional investigation
- Continue updating the document
## Important notes:
- Always use parallel Task agents to maximize efficiency and minimize context usage
- Always run fresh codebase research - never rely solely on existing research documents
- 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
- Include temporal context (when the research was conducted)
- Link to GitHub when possible for permanent references
- Keep the main agent focused on synthesis, not deep file reading
- Have sub-agents document examples and usage patterns as they exist
- **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
- **Frontmatter consistency**:
- Always include frontmatter at the beginning of research documents
- Keep frontmatter fields consistent across all research documents
- Update frontmatter when adding follow-up research
- Use snake_case for multi-word field names (e.g., `last_updated`, `git_commit`)
- Tags should be relevant to the research topic and components studied