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feat: Add LangGraph agent implementations and restructure epic catalog
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# Never Self-Report Success - User Authority Only Rule
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**CRITICAL**: The AI agent must NEVER declare success, completion, or task finishing on its own behalf. Only the USER has the authority to determine and report success.
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## Core Principle
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**"Show Evidence, Not Conclusions - Let Users Declare Victory"**
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Every action should provide evidence of execution, but the agent must refrain from declaring that the task is complete, successful, or finished.
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## Forbidden Statements
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**NEVER** use these phrases or similar:
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- "Successfully completed"
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- "Task finished"
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- "Setup complete"
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- "Done!"
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- "All tasks completed"
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- "Integration successful"
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- "Server started successfully"
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- "Installation successful"
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- "Configuration complete"
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- "Ready to use"
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- "Everything is working"
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## Required Communication Pattern
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```python
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# FORBIDDEN: Self-declared success
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def complete_task():
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execute_action()
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return "Successfully completed the task!" # WRONG
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# REQUIRED: Evidence-based reporting
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def complete_task():
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result = execute_action()
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return f"Executed action. Output: {result}" # CORRECT - shows evidence
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```
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### Acceptable Reporting Style
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**REQUIRED**: Use neutral, evidence-based language:
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- "Executed command: `command_here`"
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- "Created file at: `path/to/file`"
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- "Updated configuration in: `config_file`"
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- "Command output: [show output]"
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- "File contents: [show contents]"
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- "Process status: [show status]"
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### User Validation Pattern
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```python
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# REQUIRED: Always end with evidence and implicit invitation for user validation
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def report_action():
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print("Command executed: pip install package")
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print("Output: Successfully installed package-1.0.0")
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print("\nPackage installation command output shown above.")
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# DO NOT ADD: "Installation successful!" or "Ready to proceed!"
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# Let the user verify and decide
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```
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## Examples
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### ❌ FORBIDDEN: Self-Declared Success
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```
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Agent: "I've successfully installed all dependencies and started the LangGraph Studio server.
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The server is now running at http://localhost:8123. Setup is complete!"
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```
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### ✅ REQUIRED: Evidence-Based Reporting
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```
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Agent: "Executed installation commands:
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- pip install langgraph-cli[inmem]
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- langgraph dev --host 0.0.0.0 --port 8123
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Command output:
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[shows actual terminal output]
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Server process status:
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[shows process list]"
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```
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## Implementation Standards
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### 1. **Command Execution Reporting**
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```python
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# FORBIDDEN
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print("Command executed successfully!")
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# REQUIRED
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print(f"Executed: {command}")
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print(f"Exit code: {exit_code}")
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print(f"Output: {output}")
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```
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### 2. **File Operations Reporting**
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```python
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# FORBIDDEN
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print("File created successfully!")
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# REQUIRED
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print(f"Created file: {file_path}")
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print(f"File contents: {contents}")
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```
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### 3. **Service Status Reporting**
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```python
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# FORBIDDEN
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print("Server started successfully and is ready!")
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# REQUIRED
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print(f"Executed: langgraph dev")
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print(f"Process ID: {pid}")
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print(f"Expected endpoint: http://localhost:8123")
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```
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## Enforcement Standards
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This rule is **ALWAYS ACTIVE** and applies to:
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- All command executions and outputs
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- All file creation and modification reports
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- All service startup and status checks
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- All installation and configuration tasks
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- All testing and validation activities
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- All communication with the user
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### Blocking Conditions
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The following phrases will BLOCK any response:
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1. **Success Claims**: Any statement declaring success without user validation
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2. **Completion Claims**: Any statement declaring task completion
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3. **Readiness Claims**: Any statement declaring systems are "ready" or "working"
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4. **Finishing Claims**: Any statement declaring work is "done" or "finished"
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## Remember
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**"I execute and report evidence. The user validates and declares success."**
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**"My role is to show, not to conclude."**
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**"Evidence speaks, users judge."**
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This rule ensures humility, accuracy, and proper authority distribution between AI agent execution and human validation.
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# No Unsolicited Reports Rule
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**CRITICAL**: Do NOT create summary reports, status documents, completion reports, migration summaries, or analysis documents unless the user EXPLICITLY requests them.
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## Core Principle
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**"Implementation First, Reports Only When Asked"**
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Users want **working code and systems**, not meta-documentation about what you did. Focus on implementation work, not self-reporting.
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## What NOT to Create (Unless Asked)
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❌ **Forbidden Without Explicit Request**:
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- Migration completion reports
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- Status summaries
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- Work completion documents
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- Implementation analysis documents
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- "What we accomplished" summaries
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- "Next steps" planning documents
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- Progress reports
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- Achievement summaries
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- Any document that describes work done rather than technical documentation
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## What TO Create (Without Being Asked)
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✅ **Always Create**:
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- Code files
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- Configuration files
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- Technical documentation (README.md, API docs)
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- Inline code comments
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- Error handling
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- Tests
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✅ **Create When Stale**:
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- README.md updates when features change
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- API documentation when interfaces change
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- Architecture docs when design changes
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- Integration guides when dependencies change
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## User Phrases That Mean "Create a Report"
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Only create reports when user says:
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- "create a report"
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- "write a summary"
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- "document what you did"
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- "summarize the work"
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- "create a migration report"
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- "write up the results"
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## Examples
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### ❌ WRONG (Unsolicited Report)
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```markdown
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# LangSmith Migration Complete
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## Summary
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Successfully migrated all prompts to LangSmith...
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## What Was Accomplished
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- ✅ Migrated 8 prompts
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- ✅ Created hybrid system
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...
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```
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**Why Wrong**: User didn't ask for a summary. Just do the work and stop.
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### ✅ CORRECT (Just Do the Work)
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```
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[Migrates prompts]
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[Updates code]
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[Tests system]
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User: "Looks good!"
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```
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**Why Correct**: Work is done, system works. No unsolicited report needed.
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### ✅ CORRECT (When User Asks)
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User: "Can you summarize what you just did?"
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```markdown
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# Migration Summary
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Migrated 8 prompts to LangSmith...
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```
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**Why Correct**: User explicitly requested a summary.
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## Enforcement
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**Before creating ANY document**, ask:
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1. Is this technical documentation needed for the system to work?
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2. Did the user explicitly ask for this report/summary?
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If both answers are NO → **Don't create it!**
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## Remember
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**"Users want action, not reports about action."**
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**"Show, don't tell."**
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**"Code speaks louder than status documents."**

.gitignore

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.streamlit/
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.streamlit/secrets.toml
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# LangGraph / LangGraph Studio
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.langgraph_api/
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.langgraph/
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langgraph_storage/
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.langgraph_checkpoints/
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langgraph_data/
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# Temporary files
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*.tmp
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*.temp

LANGGRAPH_CONVERSION_PLAN.md

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# LangGraph Conversion Plan
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## Status: Converting all agents to LangGraph compatibility
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### ✅ Completed (Already LangGraph Compatible)
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- [x] requirements_analyst_langgraph.py (Pydantic BaseModel ✓)
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- [x] architecture_designer_langgraph.py (Pydantic BaseModel ✓)
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- [x] code_generator_langgraph.py (Pydantic BaseModel ✓)
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- [x] rag_swarm_langgraph.py (needs Pydantic verification)
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- [x] web_research_swarm.py (needs Pydantic verification)
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### 🔄 In Progress (Need Pydantic BaseModel Conversion)
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- [ ] test_generator_langgraph.py
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- [ ] code_reviewer_langgraph.py
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- [ ] documentation_generator_langgraph.py
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- [ ] development_workflow_langgraph.py
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### 📝 To Create (Individual Research Agents)
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- [ ] query_planner_langgraph.py
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- [ ] web_search_langgraph.py
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- [ ] content_parser_langgraph.py
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- [ ] verification_langgraph.py
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- [ ] synthesis_langgraph.py
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- [ ] comprehensive_research_langgraph.py
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### 📝 To Create (Individual RAG Agents)
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- [ ] query_analyst_langgraph.py
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- [ ] retrieval_specialist_langgraph.py
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- [ ] re_ranker_langgraph.py
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- [ ] writer_langgraph.py
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- [ ] quality_assurance_langgraph.py
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- [ ] web_scraping_specialist_langgraph.py
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### 📝 To Create (Management Agents)
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- [ ] project_manager_langgraph.py
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- [ ] self_optimizing_validation_langgraph.py
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### 📝 To Create (Security Agents)
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- [ ] security_analyst_langgraph.py
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- [ ] ethical_ai_protection_langgraph.py
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### 📝 To Create (MCP Agent)
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- [ ] mcp_enhanced_langgraph.py
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### 📝 To Create (Specialized Teams)
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- [ ] specialized_subagent_team_langgraph.py
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- [ ] workflow_orchestration_team_langgraph.py
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- [ ] test_recovery_specialist_team_langgraph.py
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- [ ] database_cleanup_specialist_team_langgraph.py
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## Strategy
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1. **Phase 1**: Complete Pydantic conversion for existing LangGraph agents (4 agents)
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2. **Phase 2**: Create swarm graphs for major workflows (3 swarms)
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3. **Phase 3**: Expose top 10 most useful agents in langgraph.json
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4. **Phase 4**: Gradually add remaining agents as needed
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## langgraph.json Update Strategy
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Expose in order of importance:
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1. Development Workflow (full SDLC)
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2. Requirements Analyst (standalone)
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3. Architecture Designer (standalone)
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4. Code Generator (standalone)
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5. RAG Swarm (information retrieval)
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6. Research Swarm (web research)
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7. Test Generator (standalone)
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8. Code Reviewer (standalone)
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9. Documentation Generator (standalone)
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10. Project Manager (coordination)
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