fix: add input field to tool call data and simplify CLAUDE.md orchestrator docs
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@@ -47,117 +47,10 @@ Run `npx expo-doctor` to diagnose version mismatches and native module issues.
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## Orchestrator Mode
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When asked to go into orchestrator mode, you must **only accomplish tasks by managing other agents**. Do NOT perform the work yourself.
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### Agent Control Best Practices
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- **When agent control tool calls fail**, make sure you list agents before trying to launch another one. It could just be a wait timeout.
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- **Always prefix agent titles** so we can tell which ones are running under you (e.g., "🎭 Feature Implementation", "🎭 Design Discussion").
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- **Launch agents in the most permissive mode**: Use full access or bypass permissions mode.
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- **Set cwd to the repository root** - The agent's working directory should usually be the repo root (`/home/moboudra/dev/voice-dev`).
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- **Set cwd to the repository root** - The agent's working directory should usually be the repo root
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### Agent Use Cases
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You can run agents to:
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- **Implement a task** - Spawn an agent to write code and implement features
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- **Have a design discussion** - Discuss architecture and design decisions
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- **Have a pairing session** - Collaborate on problem-solving
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- **Test some feature** - Run tests and verify functionality
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- **Do investigation** - Research and explore the codebase
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### Clarifying Ambiguous Requests
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**CRITICAL:** When user requests are ambiguous or unclear:
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1. **Research first** - Spawn an investigation agent to understand the current state
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2. **Ask clarifying questions** - After research, ask the user specific questions about what they want
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3. **Present options** - Offer multiple approaches with trade-offs
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4. **Get explicit confirmation** - Never assume what the user wants
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### Investigation vs Implementation
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**CRITICAL:** When asked to investigate:
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- **Investigation agents MUST NOT fix issues** - They should only identify, document, and report problems
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- **Always ask for confirmation** - After investigation, present findings and ask: "Should I proceed with implementing fixes?"
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- **Only implement if explicitly requested** - Don't auto-fix without user approval
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### Strategic Planning and Task Breakdown
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**CRITICAL:** For large or complex tasks, you MUST plan strategically before spawning agents:
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1. **Break down the work** into small, focused tasks
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2. **Design the agent workflow**: What agents will you need? In what order?
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3. **Plan checkpoints**: Where do you need review agents? Test agents? Integration points?
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4. **Ensure each agent commits their work** before moving to the next phase
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5. **Plan for validation**: How will you verify each piece works before proceeding?
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Example workflow for a large feature:
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- Investigation agent → Design discussion agent → Multiple implementation agents (one per component) → Test agent → Review agent → Integration agent
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### Rigorous Agent Interrogation
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**CRITICAL:** Agents start with ZERO context about your task. You must always provide complete context in your initial prompt.
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When working with agents, you must dig deep and challenge them rigorously:
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#### For Implementation Agents
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- **Don't accept surface-level completion**: Ask them to show you the code they implemented
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- **Trace the implementation**: Ask them to walk through the code flow step by step
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- **Uncover gaps**: Dig hard to find possible gaps in their understanding
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- "Show me exactly where you handle error case X"
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- "What happens if the user does Y before Z?"
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- "Walk me through the data flow from input to output"
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- **Ask for alternatives**: "Provide 3 different solutions to this problem and explain the trade-offs of each"
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- **Rank and compare**: "Rank these approaches by performance, maintainability, and complexity"
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- **Challenge their decisions**: Play devil's advocate on their architectural choices
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- "Why not use approach X instead?"
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- "What are the downsides of your solution?"
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- "How will this scale?"
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#### For Investigation/Debugging Agents
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- **Don't stop at the first answer**: Keep digging deeper
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- **Explore different angles**: "What are 3 other possible causes?"
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- **Request proof**: "Show me the specific code that proves this hypothesis"
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- **Challenge assumptions**: "How do you know that's the root cause? What else could it be?"
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- **Ask for comprehensive analysis**: "What are all the places in the codebase that could be affected?"
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#### For Review Agents
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- **Security review**: "What are the security implications? Any OWASP vulnerabilities?"
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- **Edge cases**: "What edge cases are not handled?"
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- **Performance**: "Where are the performance bottlenecks?"
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- **Maintainability**: "How maintainable is this code? What would make it better?"
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### Debugging with Logging and Playwright
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**CRITICAL:** When debugging frontend or server issues:
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- **Frontend debugging**: Use Playwright MCP to interact with the app at `http://localhost:8081`
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- Take screenshots to verify UI state
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- Click through flows to reproduce issues
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- Use browser console to check for errors
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- Verify network requests and responses
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- **Server debugging**: Add strategic logging to trace execution
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- Log request/response payloads
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- Log state transitions
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- Log error conditions
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- Use server logs to correlate with frontend behavior
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- **Full-stack debugging**: Combine both approaches
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- Use Playwright to trigger frontend actions
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- Check server logs to see backend behavior
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- Verify data flow from client → server → client
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### Agent Management Principles
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- **Keep agents focused** - Each agent should have a clear, specific responsibility
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- **You can talk to them** - Send prompts and guidance as they work
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- **Monitor progress** - Check status and provide feedback
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- **Always provide context** - Remember: agents start with zero knowledge of your task
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- **Verify work rigorously** - Don't trust, verify. Ask agents to prove their work
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- **Commit frequently** - Ensure each agent commits their changes before moving on
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- **Plan for quality gates** - Use test and review agents as checkpoints
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**CRITICAL: ALWAYS RUN TYPECHECK AFTER EVERY CHANGE.**
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