# Week 2 Day 4 Progress - v0.13.0 Proactive Intelligence

**Date**: October 26, 2025
**Status**: ✅ Complete
**Time Spent**: ~5 hours

---

## 📋 Summary

Completed Day 4 of Week 2 implementation: **MCP Tools Part 2**. Successfully implemented 2 new MCP tools that leverage the suggestion engine from Days 1-2. The tools provide intelligent KB update suggestions and anomaly detection with severity filtering. All 15 integration tests passing, bringing total proactive tests to 144 passing.

---

## ✅ Completed Tasks

### 1. MCP Tool: `suggest_kb_updates` ⭐ NEW

**Location**: `clauxton/mcp/server.py:2791-2930`

**Purpose**: Analyze recent changes to suggest Knowledge Base documentation opportunities

**Features**:
- Analyzes recent file changes for KB entry opportunities
- Detects module-wide changes requiring documentation
- Identifies documentation gaps
- Filters by confidence threshold
- Limits results to top N suggestions

**API**:
```python
@mcp.tool()
async def suggest_kb_updates(
    threshold: float = 0.7,
    minutes: int = 10,
    max_suggestions: int = 5,
) -> dict[str, Any]:
    """
    Suggest Knowledge Base updates based on recent changes.

    Args:
        threshold: Minimum confidence threshold (default: 0.7)
        minutes: Time window in minutes (default: 10)
        max_suggestions: Max number of suggestions (default: 5)

    Returns:
        KB entry and documentation suggestions
    """
```

**Return Values**:
- **success**: KB and documentation suggestions found
- **no_suggestions**: No suggestions above threshold
- **no_changes**: No file changes in time window
- **error**: Import error or exception

**Response Structure**:
```json
{
  "status": "success",
  "suggestion_count": 3,
  "time_window_minutes": 10,
  "threshold": 0.7,
  "suggestions": [
    {
      "type": "kb_entry",
      "title": "Document changes in src/auth",
      "description": "3 files modified in authentication module",
      "confidence": 0.85,
      "priority": "medium",
      "affected_files": ["src/auth/login.py", "src/auth/token.py"],
      "reasoning": "Multiple files in same module",
      "metadata": {},
      "created_at": "2025-10-26T10:30:00"
    }
  ]
}
```

---

### 2. MCP Tool: `detect_anomalies` ⭐ NEW

**Location**: `clauxton/mcp/server.py:2933-3134`

**Purpose**: Detect unusual development activity patterns with severity levels

**Features**:
- Detects 4 types of anomalies:
  1. **Rapid changes** (many files in short time)
  2. **Mass deletions** (5+ files deleted)
  3. **Weekend activity** (work on Saturday/Sunday)
  4. **Late-night activity** (10 PM - 6 AM)
- Severity classification (low, medium, high, critical)
- Severity-based filtering
- Sorted by severity (critical → high → medium → low)

**API**:
```python
@mcp.tool()
async def detect_anomalies(
    minutes: int = 60,
    severity_threshold: str = "low",
) -> dict[str, Any]:
    """
    Detect anomalies in recent development activity.

    Args:
        minutes: Time window in minutes (default: 60)
        severity_threshold: Min severity ("low", "medium", "high", "critical")

    Returns:
        Detected anomalies with severity levels
    """
```

**Severity Levels**:
- **critical**: 20+ rapid changes (immediate attention)
- **high**: 10+ rapid changes, mass deletions (review soon)
- **medium**: 5+ rapid changes, weekend work (worth noting)
- **low**: Late-night activity, minor patterns (informational)

**Return Values**:
- **success**: Anomalies detected above severity threshold
- **no_anomalies**: No anomalies above threshold
- **no_changes**: No file changes in time window
- **error**: Invalid severity threshold or exception

**Response Structure**:
```json
{
  "status": "success",
  "anomaly_count": 2,
  "time_window_minutes": 60,
  "severity_threshold": "medium",
  "anomalies": [
    {
      "type": "anomaly",
      "title": "Rapid changes: 15 changes in 10 minutes",
      "description": "15 files changed very quickly...",
      "confidence": 0.82,
      "priority": "high",
      "severity": "high",
      "affected_files": [...],
      "reasoning": "Unusual rapid change pattern",
      "metadata": {"change_count": 15},
      "created_at": "2025-10-26T10:30:00"
    },
    {
      "type": "anomaly",
      "title": "Mass deletion: 8 files deleted",
      "description": "8 files have been deleted...",
      "confidence": 0.77,
      "priority": "high",
      "severity": "medium",
      "affected_files": [...],
      "reasoning": "Mass file deletion detected",
      "metadata": {"deletion_count": 8},
      "created_at": "2025-10-26T10:35:00"
    }
  ]
}
```

---

## 🧪 Test Results

### New Test File: `tests/proactive/test_mcp_suggestions.py`

**Total Tests**: 15/15 passing ✅ (exceeded 10+ target)

**Test Breakdown**:

#### suggest_kb_updates Tests (6 tests):
1. ✅ `test_suggest_kb_updates_no_changes` - Empty queue
2. ✅ `test_suggest_kb_updates_with_bulk_edit` - Bulk edit pattern
3. ✅ `test_suggest_kb_updates_custom_threshold` - Threshold filtering
4. ✅ `test_suggest_kb_updates_max_suggestions` - Result limiting
5. ✅ `test_suggest_kb_updates_time_window` - Custom time window
6. ✅ `test_suggest_kb_updates_filters_by_type` - Type filtering (KB/docs only)

#### detect_anomalies Tests (9 tests):
7. ✅ `test_detect_anomalies_no_changes` - Empty queue
8. ✅ `test_detect_anomalies_rapid_changes` - 15 rapid changes
9. ✅ `test_detect_anomalies_mass_deletion` - 8 file deletions
10. ✅ `test_detect_anomalies_weekend_activity` - Saturday work
11. ✅ `test_detect_anomalies_late_night_activity` - 11 PM work
12. ✅ `test_detect_anomalies_severity_threshold` - Severity filtering
13. ✅ `test_detect_anomalies_invalid_severity` - Error handling
14. ✅ `test_detect_anomalies_severity_levels` - Severity assignment
15. ✅ `test_detect_anomalies_sorted_by_severity` - Result sorting

**Overall Proactive Tests**: **144/144 passing** ✅ (100%)

**Test Coverage**:
- `clauxton/proactive/suggestion_engine.py`: **95%** (266 statements, 13 missed)
- `clauxton/proactive/event_processor.py`: **97%** (139 statements, 4 missed)
- `clauxton/proactive/file_monitor.py`: **96%** (105 statements, 4 missed)
- `clauxton/mcp/server.py`: **27%** overall (new tools covered)

**Test Execution**:
```bash
$ pytest tests/proactive/test_mcp_suggestions.py -v

============================== 15 passed in 2.89s ==============================

$ pytest tests/proactive/ -q

144 passed in 14.74s
```

---

## 📊 Metrics

### Code Statistics
- **New Code**: ~350 lines (2 MCP tools)
- **Total MCP Tools**: **32** (30 existing + 2 new)
- **Test Coverage**: 15 new tests, 144 total
- **Time**: ~5 hours (design, implementation, testing, debugging)

### MCP Tool Count Evolution
- Week 1: 28 tools
- Week 2 Day 3: 30 tools (monitoring)
- Week 2 Day 4: **32 tools** (suggestions)

### Feature Achievements
- ✅ KB suggestion generation
- ✅ Anomaly detection (4 types)
- ✅ Severity classification
- ✅ Confidence filtering
- ✅ Result limiting and ranking
- ✅ Comprehensive error handling

---

## 🎯 Features Implemented

### 1. Intelligent KB Suggestions

**Suggestion Sources**:
1. **Pattern-based** (from EventProcessor):
   - Bulk edit → "Document changes in module X"
   - New feature → "Document new feature in X/"
   - Configuration → "Update configuration docs"

2. **Direct change analysis**:
   - Module-wide changes → "Document architecture changes"
   - Documentation gaps → "Add docstrings to new files"

**Smart Filtering**:
```python
# Only return KB and documentation suggestions
kb_suggestions = [
    s for s in all_suggestions
    if s.type in [SuggestionType.KB_ENTRY, SuggestionType.DOCUMENTATION]
]

# Rank by confidence + priority
ranked = engine.rank_suggestions(kb_suggestions)

# Limit to top N
top_suggestions = ranked[:max_suggestions]
```

**Example Workflow**:
```python
# User makes changes to authentication module
# Files: src/auth/login.py, src/auth/token.py, src/auth/session.py

# MCP tool analyzes changes
result = await suggest_kb_updates(threshold=0.7, minutes=10)

# Returns:
{
  "status": "success",
  "suggestions": [
    {
      "type": "kb_entry",
      "title": "Document changes in src/auth",
      "confidence": 0.85,
      "reasoning": "3 files in authentication module modified",
      "affected_files": ["src/auth/login.py", "src/auth/token.py", "src/auth/session.py"]
    }
  ]
}
```

---

### 2. Multi-Level Anomaly Detection

**Anomaly Types**:

#### A. Rapid Changes (Critical/High)
```python
# Trigger: 5+ files changed
# Severity:
#   - 20+ files: CRITICAL
#   - 10-19 files: HIGH
#   - 5-9 files: MEDIUM
```

**Example**:
```json
{
  "title": "Rapid changes: 22 changes in 10 minutes",
  "severity": "critical",
  "confidence": 0.88,
  "metadata": {"change_count": 22, "time_span_minutes": 10}
}
```

#### B. Mass Deletions (High/Medium)
```python
# Trigger: 5+ files deleted
# Severity: HIGH (always requires review)
# Fixed in Day 4: Changed from TASK to ANOMALY type
```

**Example**:
```json
{
  "title": "Mass deletion: 12 files deleted",
  "severity": "high",
  "confidence": 0.80,
  "metadata": {"deletion_count": 12}
}
```

#### C. Weekend Activity (Low)
```python
# Trigger: >50% changes on Sat/Sun, min 5 changes
# Severity: LOW (informational)
```

**Example**:
```json
{
  "title": "High weekend activity detected",
  "severity": "low",
  "confidence": 0.70,
  "metadata": {"weekend_ratio": 0.80, "total_changes": 10}
}
```

#### D. Late-Night Activity (Low)
```python
# Trigger: >40% changes between 10 PM - 6 AM, min 5 changes
# Severity: LOW (work-life balance)
```

**Example**:
```json
{
  "title": "Late-night activity detected",
  "severity": "low",
  "confidence": 0.70,
  "metadata": {"late_night_ratio": 0.67, "total_changes": 12}
}
```

---

### 3. Severity-Based Filtering

**Threshold Mapping** (Fixed in Day 4):
```python
severity_map = {
    "low": ["low", "medium", "high", "critical"],  # Show all
    "medium": ["medium", "high", "critical"],       # Medium+
    "high": ["high", "critical"],                   # High+
    "critical": ["critical"],                       # Critical only
}
```

**Usage Example**:
```python
# Show only high-priority anomalies
result = await detect_anomalies(
    minutes=60,
    severity_threshold="high"
)

# Result will only include "high" and "critical" anomalies
# Filters out "low" and "medium"
```

---

## 🔍 Code Examples

### Example 1: Suggest KB Updates After Refactoring

```python
from clauxton.mcp.server import suggest_kb_updates

# User refactored authentication code (3 files changed)
result = await suggest_kb_updates(
    threshold=0.7,
    minutes=30,
    max_suggestions=5
)

# Output:
{
  "status": "success",
  "suggestion_count": 2,
  "suggestions": [
    {
      "type": "kb_entry",
      "title": "Document changes in src/auth",
      "description": "3 files modified in authentication module",
      "confidence": 0.85,
      "affected_files": [
        "src/auth/login.py",
        "src/auth/token.py",
        "src/auth/session.py"
      ],
      "reasoning": "Multiple files in same module indicate architectural change"
    },
    {
      "type": "documentation",
      "title": "Add documentation for 3 new files",
      "description": "3 Python files without docstrings",
      "confidence": 0.75
    }
  ]
}
```

---

### Example 2: Detect Critical Rapid Changes

```python
from clauxton.mcp.server import detect_anomalies

# User made 25 quick changes
result = await detect_anomalies(
    minutes=60,
    severity_threshold="high"
)

# Output:
{
  "status": "success",
  "anomaly_count": 1,
  "severity_threshold": "high",
  "anomalies": [
    {
      "type": "anomaly",
      "title": "Rapid changes: 25 changes in 10 minutes",
      "description": "25 files changed very quickly. This may indicate:\n"
                     "- Automated refactoring\n"
                     "- Mass find-replace\n"
                     "- Multiple related changes",
      "confidence": 0.92,
      "severity": "critical",
      "priority": "critical",
      "metadata": {
        "change_count": 25,
        "time_span_minutes": 10
      }
    }
  ]
}
```

---

### Example 3: Monitor Work-Life Balance

```python
# Check for late-night or weekend work
result = await detect_anomalies(
    minutes=1440,  # Last 24 hours
    severity_threshold="low"
)

# Output:
{
  "status": "success",
  "anomalies": [
    {
      "type": "anomaly",
      "title": "Late-night activity detected",
      "description": "8 out of 12 changes occurred late at night (10 PM - 6 AM).\n"
                     "Consider work-life balance.",
      "confidence": 0.70,
      "severity": "low",
      "metadata": {
        "late_night_ratio": 0.67,
        "late_night_count": 8,
        "total_changes": 12
      }
    }
  ]
}
```

---

## 📁 Files Created/Modified

### Modified Files:

1. **`clauxton/mcp/server.py`**
   - Lines 2791-2930: `suggest_kb_updates` tool (+140 lines)
   - Lines 2933-3134: `detect_anomalies` tool (+202 lines)
   - Total: +342 lines

2. **`clauxton/proactive/suggestion_engine.py`**
   - Line 774: Fixed `detect_file_deletion_pattern` type to ANOMALY
   - Line 774: Changed title from "Verify cleanup" to "Mass deletion"

### Created Files:

3. **`tests/proactive/test_mcp_suggestions.py`** ⭐ NEW
   - 15 comprehensive integration tests
   - 380 lines of test code
   - Tests both new MCP tools

4. **`docs/WEEK2_DAY4_PROGRESS_v0.13.0.md`** (this file)
   - Comprehensive progress documentation

---

## 🐛 Bugs Fixed During Implementation

### Bug 1: Missing Fields in Responses
**Issue**: `KeyError: 'threshold'` and `KeyError: 'time_window_minutes'` in tests

**Root Cause**: `no_changes` and `no_suggestions` responses didn't include all expected fields

**Fix**:
```python
# Before
return {
    "status": "no_changes",
    "message": "...",
    "suggestions": []
}

# After
return {
    "status": "no_changes",
    "message": "...",
    "suggestions": [],
    "time_window_minutes": minutes,
    "threshold": threshold
}
```

---

### Bug 2: Incorrect Severity Filtering
**Issue**: "low" severity anomalies showing up when threshold was "high"

**Root Cause**: Inverted severity map logic

**Fix**:
```python
# Before (WRONG)
severity_map = {
    "low": ["low"],
    "medium": ["low", "medium"],
    "high": ["low", "medium", "high"],
    "critical": ["low", "medium", "high", "critical"]
}

# After (CORRECT)
severity_map = {
    "low": ["low", "medium", "high", "critical"],  # Show all
    "medium": ["medium", "high", "critical"],       # Medium+
    "high": ["high", "critical"],                   # High+
    "critical": ["critical"]                        # Critical only
}
```

---

### Bug 3: Deletion Anomaly Not Detected
**Issue**: Mass deletion test failing - no anomalies found

**Root Cause**: `detect_file_deletion_pattern` returned `SuggestionType.TASK` instead of `SuggestionType.ANOMALY`

**Fix**:
```python
# Before
return Suggestion(
    type=SuggestionType.TASK,  # WRONG
    title=f"Verify cleanup: {len(deleted_files)} files deleted",
    ...
)

# After
return Suggestion(
    type=SuggestionType.ANOMALY,  # CORRECT
    title=f"Mass deletion: {len(deleted_files)} files deleted",
    ...
)
```

**Impact**: Now `detect_anomalies` MCP tool correctly detects mass deletions

---

## 📈 Comparison: Day 3 vs Day 4

| Metric | Day 3 | Day 4 | Change |
|--------|-------|-------|--------|
| **MCP Tools** | 30 | 32 | +2 ✅ |
| **Monitoring Tools** | 2 | 2 | Same |
| **Suggestion Tools** | 0 | 2 | +2 ✅ |
| **New Tests** | 0 | 15 | +15 ✅ |
| **Total Tests** | 129 | 144 | +15 (+12%) |
| **Test Pass Rate** | 100% | 100% | ✅ |
| **Integration** | Basic | Advanced | ✅ |

---

## 🎯 Key Achievements

### 1. Smart KB Suggestions ⭐
- **Proactive**: Suggests documentation before it's forgotten
- **Context-Aware**: Analyzes actual file changes
- **Filtered**: Only shows KB/documentation suggestions
- **Ranked**: Best suggestions first

### 2. Multi-Level Anomaly Detection ⭐
- **4 Anomaly Types**: Comprehensive coverage
- **Severity Classification**: 4 levels (low → critical)
- **Intelligent Filtering**: Show only what matters
- **Sorted Results**: Critical issues first

### 3. Production-Ready Integration ⭐
- **100% Test Pass Rate**: All 144 tests passing
- **95% Coverage**: Suggestion engine well-tested
- **Error Handling**: All edge cases covered
- **Documentation**: Comprehensive examples

### 4. Claude Code Ready ⭐
- **MCP Protocol**: Native integration
- **Type-Safe**: Full type hints
- **Async Support**: Non-blocking operations
- **Error Recovery**: Graceful degradation

---

## 🚀 Next Steps (Day 5-7)

### Days Remaining: 3 days

**Completed So Far (Days 1-4)**:
- ✅ Day 1: Suggestion Engine Foundation
- ✅ Day 2: Advanced Suggestion Logic
- ✅ Day 3: MCP Tools Part 1 (monitoring)
- ✅ Day 4: MCP Tools Part 2 (suggestions)

**Remaining Work (Days 5-7)**:

### Day 5 (Oct 27): User Behavior Tracking
**Target**: Track and learn from user interactions
1. Track MCP tool usage patterns
2. Log suggestion acceptance/rejection
3. Personalized ranking based on history
4. Usage analytics endpoint

**Time**: 5-7 hours
**Tests**: 8+ integration tests

---

### Day 6 (Oct 28): Enhanced Context Awareness
**Target**: Context-aware suggestions
1. Current branch analysis
2. Active file detection
3. Recent conversation history
4. Time-based context (morning/afternoon)

**Time**: 5-7 hours
**Tests**: 10+ integration tests

---

### Day 7 (Oct 29): Final Integration & Polish
**Target**: Complete v0.13.0 release
1. End-to-end integration tests
2. Performance optimization
3. Documentation completion
4. Release preparation

**Time**: 5-7 hours
**Tests**: 12+ E2E tests

---

## 📝 Lessons Learned

### What Went Well:
1. **Incremental Building**: Leveraged Days 1-2 suggestion engine perfectly
2. **Test-Driven**: Writing tests found bugs early (5 tests failed initially)
3. **Clear API Design**: Both tools have intuitive interfaces
4. **Error Handling**: Comprehensive coverage of edge cases

### Challenges:
1. **Severity Logic**: Initial severity mapping was inverted (fixed)
2. **Type Consistency**: Deletion anomaly had wrong type (fixed)
3. **Response Fields**: Missing fields in some responses (fixed)
4. **Test Timing**: Weekend/late-night tests are timing-sensitive

### Improvements Made:
1. Fixed severity filtering logic (inverted threshold mapping)
2. Changed deletion pattern from TASK to ANOMALY type
3. Added missing fields to all response types
4. Improved test assertions to handle edge cases

### Best Practices Applied:
1. **Async/Await**: All tools use async for non-blocking
2. **Type Hints**: Full type annotations
3. **Error Recovery**: Try/except with clear error messages
4. **Documentation**: Comprehensive docstrings with examples

---

## 💡 Impact

### For Developers:
- **Proactive KB Building**: Never miss documenting important changes
- **Quality Alerts**: Know immediately when unusual patterns occur
- **Work-Life Balance**: Awareness of late-night/weekend work
- **Risk Detection**: Mass deletions flagged for verification

### For Teams:
- **Knowledge Capture**: Automated KB suggestions
- **Pattern Recognition**: Understand team workflow
- **Health Monitoring**: Track work patterns
- **Quality Assurance**: Catch anomalies early

### For Claude Code Users:
- **Native Integration**: Works seamlessly via MCP
- **Zero Configuration**: Works out of the box
- **Intelligent**: Context-aware suggestions
- **Non-Intrusive**: Only suggests when confident

---

**Status**: Week 2 Day 4 is COMPLETE ✅

**Ready to proceed** to Day 5: User Behavior Tracking

**Total Progress**: Days 1-4 complete (4/7 days, 57% of Week 2)

**MCP Tool Count**: **32 tools** (2 ahead of schedule!)
