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- Update workflow-architecture.md: Streamline structure, enforce 10-task hard limit - Update workflow plan.md: Add file cohesion rules, similar functionality warnings - Update task breakdown.md: Manual breakdown controls, conflict detection - Update task-core.md: Sync JSON schema with workflow-architecture.md - Establish consistent 10-task maximum across all workflow commands - Add file cohesion enforcement to prevent splitting related files - Replace "Complex" classification with "Over-scope" requiring re-planning 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
238 lines
8.7 KiB
Markdown
238 lines
8.7 KiB
Markdown
---
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name: plan-deep
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description: Deep technical planning with Gemini CLI analysis and action-planning-agent
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usage: /workflow:plan-deep <task_description>
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argument-hint: "task description" | requirements.md
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examples:
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- /workflow:plan-deep "Refactor authentication system to use JWT"
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- /workflow:plan-deep "Implement real-time notifications across modules"
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- /workflow:plan-deep requirements.md
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---
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# Workflow Plan Deep Command (/workflow:plan-deep)
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## Overview
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Creates comprehensive implementation plans through deep codebase analysis using Gemini CLI and the action-planning-agent. This command enforces multi-dimensional context gathering before planning, ensuring technical decisions are grounded in actual codebase understanding.
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## Key Differentiators
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### vs /workflow:plan
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| Feature | /workflow:plan | /workflow:plan-deep |
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|---------|---------------|-------------------|
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| **Analysis Depth** | Basic requirements extraction | Deep codebase analysis |
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| **Gemini CLI** | Optional | **Mandatory (via agent)** |
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| **Context Scope** | Current input only | Multi-dimensional analysis |
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| **Agent Used** | None (direct processing) | action-planning-agent |
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| **Output Detail** | Standard IMPL_PLAN | Enhanced hierarchical plan |
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| **Best For** | Quick planning | Complex technical tasks |
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## When to Use This Command
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### Ideal Scenarios
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- **Cross-module refactoring** requiring understanding of multiple components
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- **Architecture changes** affecting system-wide patterns
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- **Complex feature implementation** spanning >3 modules
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- **Performance optimization** requiring deep code analysis
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- **Security enhancements** needing comprehensive vulnerability assessment
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- **Technical debt resolution** with broad impact
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### Not Recommended For
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- Simple, single-file changes
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- Documentation updates
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- Configuration adjustments
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- Tasks with clear, limited scope
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## Execution Flow
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### 1. Input Processing
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```
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Input Analysis:
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├── Validate input clarity (reject vague descriptions)
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├── Parse task description or file
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├── Extract key technical terms
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├── Identify potential affected domains
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└── Prepare context for agent
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```
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**Clarity Requirements**:
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- **Minimum specificity**: Must include clear technical goal and affected components
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- **Auto-rejection**: Vague inputs like "optimize system", "refactor code", "improve performance" without context
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- **Response**: `❌ Input too vague. Deep planning requires specific technical objectives and component scope.`
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### 2. Agent Invocation with Deep Analysis Flag
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The command invokes action-planning-agent with special parameters that **enforce** Gemini CLI analysis.
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### 3. Agent Processing (Delegated to action-planning-agent)
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**Agent Execution Flow**:
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```
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Agent receives DEEP_ANALYSIS_REQUIRED flag
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├── Executes 4-dimension Gemini CLI analysis in parallel:
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│ ├── Architecture Analysis (patterns, components)
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│ ├── Code Pattern Analysis (conventions, standards)
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│ ├── Impact Analysis (affected modules, dependencies)
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│ └── Testing Requirements (coverage, patterns)
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├── Consolidates Gemini results into gemini-analysis.md
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├── Creates workflow session directory
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├── Generates hierarchical IMPL_PLAN.md
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├── Creates TODO_LIST.md for tracking
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└── Saves all outputs to .workflow/WFS-[session-id]/
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```
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```markdown
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Task(action-planning-agent):
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description: "Deep technical planning with mandatory codebase analysis"
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prompt: |
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Create implementation plan for: [task_description]
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EXECUTION MODE: DEEP_ANALYSIS_REQUIRED
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MANDATORY REQUIREMENTS:
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- Execute comprehensive Gemini CLI analysis (4 dimensions)
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- Skip PRD processing (no PRD provided)
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- Skip session inheritance (standalone planning)
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- Force FLOW_CONTROL flag = true
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- Set pre_analysis = multi-step array format with comprehensive analysis steps
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- Generate hierarchical task decomposition (max 2 levels: IMPL-N.M)
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- Create detailed IMPL_PLAN.md with subtasks
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- Generate TODO_LIST.md for tracking
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GEMINI ANALYSIS DIMENSIONS (execute in parallel):
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1. Architecture Analysis - design patterns, component relationships
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2. Code Pattern Analysis - conventions, error handling, validation
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3. Impact Analysis - affected modules, breaking changes
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4. Testing Requirements - coverage needs, test patterns
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FOCUS: Technical implementation based on deep codebase understanding
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```
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### 4. Output Generation (by Agent)
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The action-planning-agent generates in `.workflow/WFS-[session-id]/`:
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- **IMPL_PLAN.md** - Hierarchical implementation plan with stages
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- **TODO_LIST.md** - Unified hierarchical task tracking with ▸ container tasks and indented subtasks
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- **.task/*.json** - Task definitions for complex projects
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- **workflow-session.json** - Session tracking
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- **gemini-analysis.md** - Consolidated Gemini analysis results
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## Command Processing Logic
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```python
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def process_plan_deep_command(input):
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# Step 1: Parse input
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task_description = parse_input(input)
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# Step 2: Build agent prompt with deep analysis flag
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agent_prompt = f"""
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EXECUTION_MODE: DEEP_ANALYSIS_REQUIRED
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TASK: {task_description}
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MANDATORY FLAGS:
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- FLOW_CONTROL = true
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- pre_analysis = multi-step array format for comprehensive pre-analysis
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- FORCE_PARALLEL_ANALYSIS = true
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- SKIP_PRD = true
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- SKIP_SESSION_INHERITANCE = true
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Execute comprehensive Gemini CLI analysis before planning.
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"""
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# Step 3: Invoke action-planning-agent
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# Agent will handle session creation and Gemini execution
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Task(
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subagent_type="action-planning-agent",
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description="Deep technical planning with mandatory analysis",
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prompt=agent_prompt
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)
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# Step 4: Agent handles all processing and outputs
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return "Agent executing deep analysis and planning..."
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```
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## Error Handling
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### Common Issues and Solutions
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**Input Processing Errors**
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- **Vague text input**: Auto-reject without guidance
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- Rejected examples: "optimize system", "refactor code", "make it faster", "improve architecture"
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- Response: Direct rejection message, no further assistance
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**Agent Execution Errors**
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- Verify action-planning-agent availability
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- Check for context size limits
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- Agent handles Gemini CLI failures internally
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**Gemini CLI Failures (handled by agent)**
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- Agent falls back to file-pattern based analysis
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- Agent retries with reduced scope automatically
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- Agent alerts if critical analysis fails
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**File Access Issues**
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- Verify permissions for workflow directory
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- Check file patterns for validity
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- Alert on missing CLAUDE.md files
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## Integration Points
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### Related Commands
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- `/workflow:plan` - Quick planning without deep analysis
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- `/workflow:execute` - Execute generated plans
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- `/workflow:review` - Review implementation progress
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- `/context` - View generated planning documents
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### Agent Dependencies
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- **action-planning-agent** - Core planning engine
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- **code-developer** - For execution phase
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- **code-review-agent** - For quality checks
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## Usage Examples
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### Example 1: Cross-Module Refactoring
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```bash
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/workflow:plan-deep "Refactor user authentication to use JWT tokens across all services"
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```
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Generates comprehensive plan analyzing:
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- Current auth implementation
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- All affected services
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- Migration strategy
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- Testing requirements
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### Example 2: Performance Optimization
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```bash
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/workflow:plan-deep "Optimize database query performance in reporting module"
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```
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Creates detailed plan including:
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- Current query patterns analysis
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- Bottleneck identification
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- Optimization strategies
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- Performance testing approach
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### Example 3: Architecture Enhancement
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```bash
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/workflow:plan-deep "Implement event-driven architecture for order processing"
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```
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Produces hierarchical plan with:
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- Current architecture assessment
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- Event flow design
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- Module integration points
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- Staged migration approach
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## Best Practices
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1. **Use for Complex Tasks**: Reserve for tasks requiring deep understanding
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2. **Provide Clear Descriptions**: Specific task descriptions yield better analysis
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3. **Review Gemini Output**: Check analysis results for accuracy
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4. **Iterate on Plans**: Refine based on initial analysis
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5. **Track Progress**: Use generated TODO_LIST.md for execution
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## Technical Notes
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- **Agent-Driven Analysis**: action-planning-agent executes all Gemini CLI commands
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- **Parallel Execution**: Agent runs 4 Gemini analyses concurrently for performance
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- **Context Management**: Agent handles context size limits automatically
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- **Structured Handoff**: Command passes DEEP_ANALYSIS_REQUIRED flag to agent
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- **Session Management**: Agent creates and manages workflow session
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- **Output Standards**: All documents follow established workflow formats
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---
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**System ensures**: Deep technical understanding before planning through mandatory Gemini CLI analysis and intelligent agent orchestration |