How long does the integration take?

Change one base URL in an OpenAI-compatible client, or install the Python or TypeScript SDK; the quickstart routes a first request in a few minutes.

Will this lock us into another vendor?

No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.

What happens when a provider fails?

The router falls back to the next model your policy allows and records the fallback in the trace, so an outage costs a retry, not an incident.

fleeting-note-lifecycle-workflow - Prompt

Name: fleeting-note-lifecycle-workflow
Author: thaddiusatme

Prompt file imported from thaddiusatme/inneros-zettelkasten (.windsurf/workflows/fleeting-note-lifecycle-workflow.md). Copyright stays with the author.

Fleeting Note Lifecycle Workflow: Phase 5.6 Extension

Purpose: Systematic TDD implementation of fleeting note lifecycle management
Integration: Extends existing Phase 5 AI workflows and WorkflowManager infrastructure
Reference: Projects/fleeting-note-lifecycle-mvp-manifest.md

🎯 Workflow Overview

Project Type: Phase 5.6 Integration Extension

Extends: Existing WorkflowManager, CLI infrastructure, AI processing pipeline
Preserves: All existing functionality (66/66 tests must remain passing)
Adds: Systematic fleeting note aging, quality triage, promotion workflows
Follows: Integration Project Workflow methodology

Implementation Philosophy

TDD-First: Red → Green → Refactor cycles for all new features
Integration-First: Build on existing infrastructure, don't duplicate
Safety-First: Use proven DirectoryOrganizer patterns with backups
User-First: Follow existing CLI patterns and output formatting

📋 Phase Implementation Workflow

Phase 1: Foundation (Week 1)

Goal: Implement US-1 Fleeting Note Age Detection

Step 1: Pre-Implementation Validation

// turbo
# Ensure clean baseline before starting
cd /Users/thaddius/repos/inneros-zettelkasten
python3 -m pytest development/tests/ -v

Expected: All existing tests pass (establish baseline)

Step 2: TDD RED Phase - Create Failing Tests

# Create test file for fleeting analysis features
touch development/tests/unit/test_fleeting_lifecycle.py

# Write failing tests for:
# - FleetingAnalysis data structure
# - analyze_fleeting_notes() method  
# - generate_fleeting_health_report() method
# - CLI --fleeting-health integration

Step 3: TDD GREEN Phase - Minimal Implementation

# Extend WorkflowManager with minimal fleeting methods
# Add CLI flag to dedicated fleeting_cli.py (ADR-004)
# Implement just enough to pass tests

# Verify tests pass:
python3 -m pytest development/tests/unit/test_fleeting_lifecycle.py -v

Step 4: TDD REFACTOR Phase - Enhanced Features

# Add error handling, performance optimization
# Enhance output formatting to match existing patterns
# Add comprehensive docstrings and type hints

# Verify all tests still pass:
python3 -m pytest development/tests/ -v

Step 5: Real Data Validation

# Test with actual fleeting notes collection
python3 development/src/cli/fleeting_cli.py fleeting-health

# Verify performance <3 seconds
time python3 development/src/cli/fleeting_cli.py fleeting-health

Step 6: Documentation & Integration

# Update CLI reference
# Add to README.md
# Document integration patterns used

# Commit clean implementation
git add -A
git commit -m "feat(fleeting): implement age detection and health reporting (US-1)

- Add WorkflowManager.analyze_fleeting_notes() method
- Add WorkflowManager.generate_fleeting_health_report() method  
- Add CLI --fleeting-health flag with summary stats
- Include TDD test suite with 5-8 comprehensive tests
- Performance: <3 seconds for 100+ notes
- Integration: Uses existing metadata parsing, follows CLI patterns"

Phase 2: AI Triage (Week 1-2)

Goal: Implement US-2 Quality-Based Fleeting Triage

TDD Process:

RED: Tests for AI-powered triage recommendations
GREEN: Integration with existing quality scoring pipeline
REFACTOR: Checklist output formatting, JSON export support

Key Integration Points:

Reuse process_inbox_note() quality scoring infrastructure
Follow generate_weekly_recommendations() patterns
Use existing AI graceful fallback mechanisms

Phase 3: Promotion Workflow (Week 2)

Goal: Implement US-3 Simple Promotion Workflow

TDD Process:

RED: Tests for safe fleeting note promotion
GREEN: Integration with DirectoryOrganizer (P0+P1 system)
REFACTOR: Comprehensive safety features and validation

Key Integration Points:

Use existing promote_note() method with fleeting routing
Leverage DirectoryOrganizer backup and rollback capabilities
Maintain existing link integrity preservation (P0-3 system)

🔧 Technical Implementation Patterns

Extend WorkflowManager (Don't Replace)

class WorkflowManager:
    # Existing methods - PRESERVE ALL ✅
    def __init__(self, ...)
    def process_inbox_note(self, ...)
    def generate_weekly_recommendations(self, ...)
    def promote_note(self, ...)
    
    # NEW: Fleeting lifecycle extensions ➕
    def analyze_fleeting_notes(self) -> FleetingAnalysis:
        """Scan fleeting notes and analyze age distribution."""
        
    def generate_fleeting_health_report(self) -> Dict:
        """Generate health report for fleeting notes collection."""
        
    def generate_fleeting_triage_recommendations(self) -> Dict:
        """Generate AI-powered triage recommendations."""
        
    def promote_fleeting_note(self, note_path: str) -> Dict:
        """Safely promote fleeting note to permanent status."""

CLI Integration Pattern

# Use dedicated fleeting_cli.py (ADR-004, October 2025)
# Commands available:
python3 development/src/cli/fleeting_cli.py fleeting-health
python3 development/src/cli/fleeting_cli.py fleeting-triage
python3 development/src/cli/fleeting_cli.py promote-note PATH

# Core workflow commands in core_workflow_cli.py:
python3 development/src/cli/core_workflow_cli.py promote note.md permanent

Data Structure Patterns

# Follow existing dataclass patterns from analytics.py
@dataclass
class FleetingAnalysis:
    total_notes: int
    age_distribution: Dict[str, int]
    oldest_note: Optional[Dict]
    recommendations_count: int
    generated_at: str

🧪 Testing Strategy

Unit Tests (Following Existing Patterns)

# development/tests/unit/test_fleeting_lifecycle.py
class TestFleetingLifecycle:
    def test_analyze_fleeting_notes_empty_directory(self):
    def test_analyze_fleeting_notes_with_valid_notes(self):
    def test_generate_health_report_structure(self):
    def test_age_categorization_accuracy(self):
    def test_cli_fleeting_health_integration(self):

Integration Tests

# development/tests/integration/test_fleeting_integration.py  
class TestFleetingIntegration:
    def test_fleeting_triage_uses_existing_ai_pipeline(self):
    def test_promotion_uses_directory_organizer_safety(self):
    def test_performance_benchmarks_maintained(self):

Performance Validation

# Benchmark commands (must maintain existing performance)
time python3 development/src/cli/weekly_review_cli.py weekly-review
time python3 development/src/cli/fleeting_cli.py fleeting-health
time python3 development/src/cli/fleeting_cli.py fleeting-triage

🔒 Safety & Validation Checklist

Before Each Phase

All existing tests pass (66/66 baseline)
Performance benchmarks established
No breaking changes to existing CLI commands
Git working directory clean

During Implementation

TDD cycles followed strictly (Red → Green → Refactor)
Integration patterns match existing code style
Error handling follows established patterns
Documentation updated incrementally

After Each Phase

All tests pass including new ones
Performance targets met (<3s health, <10s triage, <5s promotion)
Real data validation successful
Git commit with clear description

📊 Success Validation

Functional Validation

# Phase 1: Age detection working
python3 development/src/cli/fleeting_cli.py fleeting-health
# Should show: total notes, age distribution, oldest note, <3s execution

# Phase 2: AI triage working  
python3 development/src/cli/fleeting_cli.py fleeting-triage
# Should show: promotion recommendations, rationale, confidence scores

# Phase 3: Promotion working
python3 development/src/cli/fleeting_cli.py promote-note "Fleeting Notes/test.md"
# Should: move file safely, preserve links, update metadata

Integration Validation

# Ensure existing workflows unaffected
python3 development/src/cli/weekly_review_cli.py weekly-review
python3 development/src/cli/core_workflow_cli.py process-inbox
python3 development/src/cli/weekly_review_cli.py enhanced-metrics

# All should work exactly as before

Performance Validation

# Measure and compare to baseline
time python3 development/src/cli/analytics_demo.py . --interactive
# Should maintain existing performance benchmarks

🎯 User Acceptance Criteria

Phase 1: Health Reporting

User can quickly see which fleeting notes are getting stale
Clear age categorization (New/Recent/Stale/Old) with counts
Identify oldest notes requiring immediate attention
Fast execution encourages regular use

Phase 2: AI Triage

User gets actionable recommendations for fleeting note promotion
AI rationale helps decision-making confidence
Checklist format matches familiar weekly review workflow
JSON export enables automation integration

Phase 3: Promotion Workflow

User can safely promote notes with confidence (no data loss)
Links preserved automatically during file moves
Quick single-command promotion for high-quality notes
Integration with weekly review reduces manual overhead

🔄 Maintenance & Evolution

Monitoring Health

# Weekly validation of fleeting lifecycle health
python3 development/src/cli/fleeting_cli.py fleeting-health --export fleeting-health-$(date +%Y-%m-%d).md

# Track progression metrics over time
python3 development/src/cli/analytics_demo.py . --fleeting-trends

Iterative Improvements

Phase 4: Bulk operations for batch fleeting management
Phase 5: Archive workflow for outdated fleeting notes
Phase 6: Integration with calendar for time-based workflows

Integration Evolution

Monitor integration health with existing Phase 5 features
Track user adoption of new fleeting commands
Measure impact on overall knowledge graph quality

This workflow ensures systematic, safe implementation of fleeting note lifecycle management that enhances rather than disrupts the existing production-ready InnerOS Zettelkasten system.

# Fleeting Note Lifecycle Workflow: Phase 5.6 Extension > **Purpose**: Systematic TDD implementation of fleeting note lifecycle management > **Integration**: Extends existing Phase 5 AI workflows and WorkflowManager infrastructure > **Reference**: `Projects/fleeting-note-lifecycle-mvp-manifest.md` ## 🎯 Workflow Overview ### **Project Type**: Phase 5.6 Integration Extension - **Extends**: Existing WorkflowManager, CLI infrastructure, AI processing pipeline - **Preserves**: All existing functionality (66/66 tests must remain passing) - **Adds**: Systematic fleeting note aging, quality triage, promotion workflows - **Follows**: Integration Project Workflow methodology ### **Implementation Philosophy** - **TDD-First**: Red → Green → Refactor cycles for all new features - **Integration-First**: Build on existing infrastructure, don't duplicate - **Safety-First**: Use proven DirectoryOrganizer patterns with backups - **User-First**: Follow existing CLI patterns and output formatting ## 📋 Phase Implementation Workflow ### **Phase 1: Foundation (Week 1)** **Goal**: Implement US-1 Fleeting Note Age Detection #### **Step 1: Pre-Implementation Validation** ```bash // turbo # Ensure clean baseline before starting cd /Users/thaddius/repos/inneros-zettelkasten python3 -m pytest development/tests/ -v ``` Expected: All existing tests pass (establish baseline) #### **Step 2: TDD RED Phase - Create Failing Tests** ```bash # Create test file for fleeting analysis features touch development/tests/unit/test_fleeting_lifecycle.py # Write failing tests for: # - FleetingAnalysis data structure # - analyze_fleeting_notes() method # - generate_fleeting_health_report() method # - CLI --fleeting-health integration ``` #### **Step 3: TDD GREEN Phase - Minimal Implementation** ```bash # Extend WorkflowManager with minimal fleeting methods # Add CLI flag to dedicated fleeting_cli.py (ADR-004) # Implement just enough to pass tests # Verify tests pass: python3 -m pytest development/tests/unit/test_fleeting_lifecycle.py -v ``` #### **Step 4: TDD REFACTOR Phase - Enhanced Features** ```bash # Add error handling, performance optimization # Enhance output formatting to match existing patterns # Add comprehensive docstrings and type hints # Verify all tests still pass: python3 -m pytest development/tests/ -v ``` #### **Step 5: Real Data Validation** ```bash # Test with actual fleeting notes collection python3 development/src/cli/fleeting_cli.py fleeting-health # Verify performance <3 seconds time python3 development/src/cli/fleeting_cli.py fleeting-health ``` #### **Step 6: Documentation & Integration** ```bash # Update CLI reference # Add to README.md # Document integration patterns used # Commit clean implementation git add -A git commit -m "feat(fleeting): implement age detection and health reporting (US-1) - Add WorkflowManager.analyze_fleeting_notes() method - Add WorkflowManager.generate_fleeting_health_report() method - Add CLI --fleeting-health flag with summary stats - Include TDD test suite with 5-8 comprehensive tests - Performance: <3 seconds for 100+ notes - Integration: Uses existing metadata parsing, follows CLI patterns" ``` ### **Phase 2: AI Triage (Week 1-2)** **Goal**: Implement US-2 Quality-Based Fleeting Triage #### **TDD Process**: 1. **RED**: Tests for AI-powered triage recommendations 2. **GREEN**: Integration with existing quality scoring pipeline 3. **REFACTOR**: Checklist output formatting, JSON export support #### **Key Integration Points**: - Reuse `process_inbox_note()` quality scoring infrastructure - Follow `generate_weekly_recommendations()` patterns - Use existing AI graceful fallback mechanisms ### **Phase 3: Promotion Workflow (Week 2)** **Goal**: Implement US-3 Simple Promotion Workflow #### **TDD Process**: 1. **RED**: Tests for safe fleeting note promotion 2. **GREEN**: Integration with DirectoryOrganizer (P0+P1 system) 3. **REFACTOR**: Comprehensive safety features and validation #### **Key Integration Points**: - Use existing `promote_note()` method with fleeting routing - Leverage DirectoryOrganizer backup and rollback capabilities - Maintain existing link integrity preservation (P0-3 system) ## 🔧 Technical Implementation Patterns ### **Extend WorkflowManager (Don't Replace)** ```python class WorkflowManager: # Existing methods - PRESERVE ALL ✅ def __init__(self, ...) def process_inbox_note(self, ...) def generate_weekly_recommendations(self, ...) def promote_note(self, ...) # NEW: Fleeting lifecycle extensions ➕ def analyze_fleeting_notes(self) -> FleetingAnalysis: """Scan fleeting notes and analyze age distribution.""" def generate_fleeting_health_report(self) -> Dict: """Generate health report for fleeting notes collection.""" def generate_fleeting_triage_recommendations(self) -> Dict: """Generate AI-powered triage recommendations.""" def promote_fleeting_note(self, note_path: str) -> Dict: """Safely promote fleeting note to permanent status.""" ``` ### **CLI Integration Pattern** ```bash # Use dedicated fleeting_cli.py (ADR-004, October 2025) # Commands available: python3 development/src/cli/fleeting_cli.py fleeting-health python3 development/src/cli/fleeting_cli.py fleeting-triage python3 development/src/cli/fleeting_cli.py promote-note PATH # Core workflow commands in core_workflow_cli.py: python3 development/src/cli/core_workflow_cli.py promote note.md permanent ``` ### **Data Structure Patterns** ```python # Follow existing dataclass patterns from analytics.py @dataclass class FleetingAnalysis: total_notes: int age_distribution: Dict[str, int] oldest_note: Optional[Dict] recommendations_count: int generated_at: str ``` ## 🧪 Testing Strategy ### **Unit Tests (Following Existing Patterns)** ```python # development/tests/unit/test_fleeting_lifecycle.py class TestFleetingLifecycle: def test_analyze_fleeting_notes_empty_directory(self): def test_analyze_fleeting_notes_with_valid_notes(self): def test_generate_health_report_structure(self): def test_age_categorization_accuracy(self): def test_cli_fleeting_health_integration(self): ``` ### **Integration Tests** ```python # development/tests/integration/test_fleeting_integration.py class TestFleetingIntegration: def test_fleeting_triage_uses_existing_ai_pipeline(self): def test_promotion_uses_directory_organizer_safety(self): def test_performance_benchmarks_maintained(self): ``` ### **Performance Validation** ```bash # Benchmark commands (must maintain existing performance) time python3 development/src/cli/weekly_review_cli.py weekly-review time python3 development/src/cli/fleeting_cli.py fleeting-health time python3 development/src/cli/fleeting_cli.py fleeting-triage ``` ## 🔒 Safety & Validation Checklist ### **Before Each Phase** - [ ] All existing tests pass (66/66 baseline) - [ ] Performance benchmarks established - [ ] No breaking changes to existing CLI commands - [ ] Git working directory clean ### **During Implementation** - [ ] TDD cycles followed strictly (Red → Green → Refactor) - [ ] Integration patterns match existing code style - [ ] Error handling follows established patterns - [ ] Documentation updated incrementally ### **After Each Phase** - [ ] All tests pass including new ones - [ ] Performance targets met (<3s health, <10s triage, <5s promotion) - [ ] Real data validation successful - [ ] Git commit with clear description ## 📊 Success Validation ### **Functional Validation** ```bash # Phase 1: Age detection working python3 development/src/cli/fleeting_cli.py fleeting-health # Should show: total notes, age distribution, oldest note, <3s execution # Phase 2: AI triage working python3 development/src/cli/fleeting_cli.py fleeting-triage # Should show: promotion recommendations, rationale, confidence scores # Phase 3: Promotion working python3 development/src/cli/fleeting_cli.py promote-note "Fleeting Notes/test.md" # Should: move file safely, preserve links, update metadata ``` ### **Integration Validation** ```bash # Ensure existing workflows unaffected python3 development/src/cli/weekly_review_cli.py weekly-review python3 development/src/cli/core_workflow_cli.py process-inbox python3 development/src/cli/weekly_review_cli.py enhanced-metrics # All should work exactly as before ``` ### **Performance Validation** ```bash # Measure and compare to baseline time python3 development/src/cli/analytics_demo.py . --interactive # Should maintain existing performance benchmarks ``` ## 🎯 User Acceptance Criteria ### **Phase 1: Health Reporting** - [ ] User can quickly see which fleeting notes are getting stale - [ ] Clear age categorization (New/Recent/Stale/Old) with counts - [ ] Identify oldest notes requiring immediate attention - [ ] Fast execution encourages regular use ### **Phase 2: AI Triage** - [ ] User gets actionable recommendations for fleeting note promotion - [ ] AI rationale helps decision-making confidence - [ ] Checklist format matches familiar weekly review workflow - [ ] JSON export enables automation integration ### **Phase 3: Promotion Workflow** - [ ] User can safely promote notes with confidence (no data loss) - [ ] Links preserved automatically during file moves - [ ] Quick single-command promotion for high-quality notes - [ ] Integration with weekly review reduces manual overhead ## 🔄 Maintenance & Evolution ### **Monitoring Health** ```bash # Weekly validation of fleeting lifecycle health python3 development/src/cli/fleeting_cli.py fleeting-health --export fleeting-health-$(date +%Y-%m-%d).md # Track progression metrics over time python3 development/src/cli/analytics_demo.py . --fleeting-trends ``` ### **Iterative Improvements** - **Phase 4**: Bulk operations for batch fleeting management - **Phase 5**: Archive workflow for outdated fleeting notes - **Phase 6**: Integration with calendar for time-based workflows ### **Integration Evolution** - Monitor integration health with existing Phase 5 features - Track user adoption of new fleeting commands - Measure impact on overall knowledge graph quality --- This workflow ensures systematic, safe implementation of fleeting note lifecycle management that enhances rather than disrupts the existing production-ready InnerOS Zettelkasten system.

{ "prompt": "# Fleeting Note Lifecycle Workflow: Phase 5.6 Extension\n\n> **Purpose**: Systematic TDD implementation of fleeting note lifecycle management \n> **Integration**: Extends existing Phase 5 AI workflows and WorkflowManager infrastructure \n> **Reference**: `Projects/fleeting-note-lifecycle-mvp-manifest.md`\n\n## 🎯 Workflow Overview\n\n### **Project Type**: Phase 5.6 Integration Extension\n- **Extends**: Existing WorkflowManager, CLI infrastructure, AI processing pipeline\n- **Preserves**: All existing functionality (66/66 tests must remain passing)\n- **Adds**: Systematic fleeting note aging, quality triage, promotion workflows\n- **Follows**: Integration Project Workflow methodology\n\n### **Implementation Philosophy**\n- **TDD-First**: Red → Green → Refactor cycles for all new features\n- **Integration-First**: Build on existing infrastructure, don't duplicate\n- **Safety-First**: Use proven DirectoryOrganizer patterns with backups\n- **User-First**: Follow existing CLI patterns and output formatting\n\n## 📋 Phase Implementation Workflow\n\n### **Phase 1: Foundation (Week 1)**\n**Goal**: Implement US-1 Fleeting Note Age Detection\n\n#### **Step 1: Pre-Implementation Validation**\n```bash\n// turbo\n# Ensure clean baseline before starting\ncd /Users/thaddius/repos/inneros-zettelkasten\npython3 -m pytest development/tests/ -v\n```\n\nExpected: All existing tests pass (establish baseline)\n\n#### **Step 2: TDD RED Phase - Create Failing Tests**\n```bash\n# Create test file for fleeting analysis features\ntouch development/tests/unit/test_fleeting_lifecycle.py\n\n# Write failing tests for:\n# - FleetingAnalysis data structure\n# - analyze_fleeting_notes() method \n# - generate_fleeting_health_report() method\n# - CLI --fleeting-health integration\n```\n\n#### **Step 3: TDD GREEN Phase - Minimal Implementation**\n```bash\n# Extend WorkflowManager with minimal fleeting methods\n# Add CLI flag to dedicated fleeting_cli.py (ADR-004)\n# Implement just enough to pass tests\n\n# Verify tests pass:\npython3 -m pytest development/tests/unit/test_fleeting_lifecycle.py -v\n```\n\n#### **Step 4: TDD REFACTOR Phase - Enhanced Features**\n```bash\n# Add error handling, performance optimization\n# Enhance output formatting to match existing patterns\n# Add comprehensive docstrings and type hints\n\n# Verify all tests still pass:\npython3 -m pytest development/tests/ -v\n```\n\n#### **Step 5: Real Data Validation**\n```bash\n# Test with actual fleeting notes collection\npython3 development/src/cli/fleeting_cli.py fleeting-health\n\n# Verify performance <3 seconds\ntime python3 development/src/cli/fleeting_cli.py fleeting-health\n```\n\n#### **Step 6: Documentation & Integration**\n```bash\n# Update CLI reference\n# Add to README.md\n# Document integration patterns used\n\n# Commit clean implementation\ngit add -A\ngit commit -m \"feat(fleeting): implement age detection and health reporting (US-1)\n\n- Add WorkflowManager.analyze_fleeting_notes() method\n- Add WorkflowManager.generate_fleeting_health_report() method \n- Add CLI --fleeting-health flag with summary stats\n- Include TDD test suite with 5-8 comprehensive tests\n- Performance: <3 seconds for 100+ notes\n- Integration: Uses existing metadata parsing, follows CLI patterns\"\n```\n\n### **Phase 2: AI Triage (Week 1-2)**\n**Goal**: Implement US-2 Quality-Based Fleeting Triage\n\n#### **TDD Process**:\n1. **RED**: Tests for AI-powered triage recommendations\n2. **GREEN**: Integration with existing quality scoring pipeline \n3. **REFACTOR**: Checklist output formatting, JSON export support\n\n#### **Key Integration Points**:\n- Reuse `process_inbox_note()` quality scoring infrastructure\n- Follow `generate_weekly_recommendations()` patterns\n- Use existing AI graceful fallback mechanisms\n\n### **Phase 3: Promotion Workflow (Week 2)**\n**Goal**: Implement US-3 Simple Promotion Workflow\n\n#### **TDD Process**:\n1. **RED**: Tests for safe fleeting note promotion\n2. **GREEN**: Integration with DirectoryOrganizer (P0+P1 system)\n3. **REFACTOR**: Comprehensive safety features and validation\n\n#### **Key Integration Points**:\n- Use existing `promote_note()` method with fleeting routing\n- Leverage DirectoryOrganizer backup and rollback capabilities\n- Maintain existing link integrity preservation (P0-3 system)\n\n## 🔧 Technical Implementation Patterns\n\n### **Extend WorkflowManager (Don't Replace)**\n```python\nclass WorkflowManager:\n # Existing methods - PRESERVE ALL ✅\n def __init__(self, ...)\n def process_inbox_note(self, ...)\n def generate_weekly_recommendations(self, ...)\n def promote_note(self, ...)\n \n # NEW: Fleeting lifecycle extensions ➕\n def analyze_fleeting_notes(self) -> FleetingAnalysis:\n \"\"\"Scan fleeting notes and analyze age distribution.\"\"\"\n \n def generate_fleeting_health_report(self) -> Dict:\n \"\"\"Generate health report for fleeting notes collection.\"\"\"\n \n def generate_fleeting_triage_recommendations(self) -> Dict:\n \"\"\"Generate AI-powered triage recommendations.\"\"\"\n \n def promote_fleeting_note(self, note_path: str) -> Dict:\n \"\"\"Safely promote fleeting note to permanent status.\"\"\"\n```\n\n### **CLI Integration Pattern**\n```bash\n# Use dedicated fleeting_cli.py (ADR-004, October 2025)\n# Commands available:\npython3 development/src/cli/fleeting_cli.py fleeting-health\npython3 development/src/cli/fleeting_cli.py fleeting-triage\npython3 development/src/cli/fleeting_cli.py promote-note PATH\n\n# Core workflow commands in core_workflow_cli.py:\npython3 development/src/cli/core_workflow_cli.py promote note.md permanent\n```\n\n### **Data Structure Patterns**\n```python\n# Follow existing dataclass patterns from analytics.py\n@dataclass\nclass FleetingAnalysis:\n total_notes: int\n age_distribution: Dict[str, int]\n oldest_note: Optional[Dict]\n recommendations_count: int\n generated_at: str\n```\n\n## 🧪 Testing Strategy\n\n### **Unit Tests (Following Existing Patterns)**\n```python\n# development/tests/unit/test_fleeting_lifecycle.py\nclass TestFleetingLifecycle:\n def test_analyze_fleeting_notes_empty_directory(self):\n def test_analyze_fleeting_notes_with_valid_notes(self):\n def test_generate_health_report_structure(self):\n def test_age_categorization_accuracy(self):\n def test_cli_fleeting_health_integration(self):\n```\n\n### **Integration Tests**\n```python\n# development/tests/integration/test_fleeting_integration.py \nclass TestFleetingIntegration:\n def test_fleeting_triage_uses_existing_ai_pipeline(self):\n def test_promotion_uses_directory_organizer_safety(self):\n def test_performance_benchmarks_maintained(self):\n```\n\n### **Performance Validation**\n```bash\n# Benchmark commands (must maintain existing performance)\ntime python3 development/src/cli/weekly_review_cli.py weekly-review\ntime python3 development/src/cli/fleeting_cli.py fleeting-health\ntime python3 development/src/cli/fleeting_cli.py fleeting-triage\n```\n\n## 🔒 Safety & Validation Checklist\n\n### **Before Each Phase**\n- [ ] All existing tests pass (66/66 baseline)\n- [ ] Performance benchmarks established \n- [ ] No breaking changes to existing CLI commands\n- [ ] Git working directory clean\n\n### **During Implementation**\n- [ ] TDD cycles followed strictly (Red → Green → Refactor)\n- [ ] Integration patterns match existing code style\n- [ ] Error handling follows established patterns\n- [ ] Documentation updated incrementally\n\n### **After Each Phase**\n- [ ] All tests pass including new ones\n- [ ] Performance targets met (<3s health, <10s triage, <5s promotion)\n- [ ] Real data validation successful\n- [ ] Git commit with clear description\n\n## 📊 Success Validation\n\n### **Functional Validation**\n```bash\n# Phase 1: Age detection working\npython3 development/src/cli/fleeting_cli.py fleeting-health\n# Should show: total notes, age distribution, oldest note, <3s execution\n\n# Phase 2: AI triage working \npython3 development/src/cli/fleeting_cli.py fleeting-triage\n# Should show: promotion recommendations, rationale, confidence scores\n\n# Phase 3: Promotion working\npython3 development/src/cli/fleeting_cli.py promote-note \"Fleeting Notes/test.md\"\n# Should: move file safely, preserve links, update metadata\n```\n\n### **Integration Validation**\n```bash\n# Ensure existing workflows unaffected\npython3 development/src/cli/weekly_review_cli.py weekly-review\npython3 development/src/cli/core_workflow_cli.py process-inbox\npython3 development/src/cli/weekly_review_cli.py enhanced-metrics\n\n# All should work exactly as before\n```\n\n### **Performance Validation** \n```bash\n# Measure and compare to baseline\ntime python3 development/src/cli/analytics_demo.py . --interactive\n# Should maintain existing performance benchmarks\n```\n\n## 🎯 User Acceptance Criteria\n\n### **Phase 1: Health Reporting**\n- [ ] User can quickly see which fleeting notes are getting stale\n- [ ] Clear age categorization (New/Recent/Stale/Old) with counts\n- [ ] Identify oldest notes requiring immediate attention\n- [ ] Fast execution encourages regular use\n\n### **Phase 2: AI Triage** \n- [ ] User gets actionable recommendations for fleeting note promotion\n- [ ] AI rationale helps decision-making confidence\n- [ ] Checklist format matches familiar weekly review workflow\n- [ ] JSON export enables automation integration\n\n### **Phase 3: Promotion Workflow**\n- [ ] User can safely promote notes with confidence (no data loss)\n- [ ] Links preserved automatically during file moves\n- [ ] Quick single-command promotion for high-quality notes \n- [ ] Integration with weekly review reduces manual overhead\n\n## 🔄 Maintenance & Evolution\n\n### **Monitoring Health**\n```bash\n# Weekly validation of fleeting lifecycle health\npython3 development/src/cli/fleeting_cli.py fleeting-health --export fleeting-health-$(date +%Y-%m-%d).md\n\n# Track progression metrics over time\npython3 development/src/cli/analytics_demo.py . --fleeting-trends\n```\n\n### **Iterative Improvements**\n- **Phase 4**: Bulk operations for batch fleeting management\n- **Phase 5**: Archive workflow for outdated fleeting notes\n- **Phase 6**: Integration with calendar for time-based workflows\n\n### **Integration Evolution**\n- Monitor integration health with existing Phase 5 features\n- Track user adoption of new fleeting commands\n- Measure impact on overall knowledge graph quality\n\n---\n\nThis workflow ensures systematic, safe implementation of fleeting note lifecycle management that enhances rather than disrupts the existing production-ready InnerOS Zettelkasten system.", "variables": [], "notes": "Fleeting Note Lifecycle Management - TDD Implementation Workflow", "metadata": { "source": { "provider": "github-windsurf-workflows", "repository": "https://github.com/thaddiusatme/inneros-zettelkasten", "path": ".windsurf/workflows/fleeting-note-lifecycle-workflow.md", "ref": "d617aaabb2dbca481a5e387ff03572858310fa24", "url": "https://github.com/thaddiusatme/inneros-zettelkasten/blob/d617aaabb2dbca481a5e387ff03572858310fa24/.windsurf/workflows/fleeting-note-lifecycle-workflow.md", "key": "thaddiusatme/inneros-zettelkasten/.windsurf/workflows/fleeting-note-lifecycle-workflow.md" } } }

About

Fleeting Note Lifecycle Workflow: Phase 5.6 Extension

🎯 Workflow Overview

Project Type: Phase 5.6 Integration Extension

Implementation Philosophy

📋 Phase Implementation Workflow

Phase 1: Foundation (Week 1)

Step 1: Pre-Implementation Validation

Step 2: TDD RED Phase - Create Failing Tests

Step 3: TDD GREEN Phase - Minimal Implementation

Step 4: TDD REFACTOR Phase - Enhanced Features

Step 5: Real Data Validation

Step 6: Documentation & Integration

Phase 2: AI Triage (Week 1-2)

TDD Process:

Key Integration Points:

Phase 3: Promotion Workflow (Week 2)

TDD Process:

Key Integration Points:

🔧 Technical Implementation Patterns

Extend WorkflowManager (Don't Replace)

CLI Integration Pattern

Data Structure Patterns

🧪 Testing Strategy

Unit Tests (Following Existing Patterns)

Integration Tests

Performance Validation

🔒 Safety & Validation Checklist

Before Each Phase

During Implementation

After Each Phase

📊 Success Validation

Functional Validation

Integration Validation

Performance Validation

🎯 User Acceptance Criteria

Phase 1: Health Reporting

Phase 2: AI Triage

Phase 3: Promotion Workflow

🔄 Maintenance & Evolution

Monitoring Health

Iterative Improvements

Integration Evolution

Install fleeting-note-lifecycle-workflow and it becomes one more candidate the router can pick - when it fits.

What it costs to adopt - in engineering time.

One base URL

No vendor lock-in

Failover built in

Use it

Manifest

Reviews