docs/technical/TASKRECORDER_IMPLEMENTATION.md

# ✅ TaskRecorder Implementation Complete

**Date:** 2025-11-24  
**Status:** ✅ Fully Implemented

---

## 🎯 IMPLEMENTATION SUMMARY

TaskRecorder er nu implementeret som et intelligent task observation og automation suggestion system, der:
- Observerer alle tasks der udføres
- Lærer mønstre fra gentagne tasks
- Foreslår automation efter N observationer
- **KRITISK:** Kræver ALTID bruger-godkendelse før execution
- Agenter kan ALDRIG committe real tasks uden GO fra bruger

---

## 🔒 SECURITY MODEL

### CRITICAL RULES

1. **NEVER Auto-Execute:** Agenter kan ALDRIG udføre real tasks uden eksplicit godkendelse
2. **Always Require Approval:** Alle automation suggestions kræver bruger-godkendelse
3. **Double Check:** Execution requests tjekker approval status før execution
4. **Audit Trail:** Alle approvals og executions logges til database

---

## 📦 COMPONENTS IMPLEMENTED

### 1. TaskRecorder Core ✅
**Location:** `apps/backend/src/mcp/cognitive/TaskRecorder.ts`

**Features:**
- ✅ Task observation (automatic via event listeners)
- ✅ Pattern learning (frequency, success rate, duration)
- ✅ Automation suggestion (after 3+ observations, 70%+ success rate)
- ✅ Approval workflow (approve/reject suggestions)
- ✅ Execution tracking (all executions logged)
- ✅ Database persistence (SQLite tables)

**Key Methods:**
- `observeTask()` - Record task execution
- `checkAndSuggestAutomation()` - Auto-suggest after patterns detected
- `approveSuggestion()` - User approves automation
- `requestTaskExecution()` - Execute with approval check
- `getPendingSuggestions()` - Get suggestions awaiting approval

---

### 2. MCP Tools ✅
**Location:** `apps/backend/src/mcp/toolHandlers.ts`

**5 New MCP Tools:**

1. **`taskrecorder.get_suggestions`** - Get pending automation suggestions
   - Returns all suggestions awaiting approval
   - Includes confidence, observed count, estimated benefit

2. **`taskrecorder.approve`** - Approve automation suggestion
   - **CRITICAL:** Only way to approve automation
   - Records approval in database
   - Enables execution (but still requires approval per execution)

3. **`taskrecorder.reject`** - Reject automation suggestion
   - Marks suggestion as rejected
   - Prevents further automation attempts

4. **`taskrecorder.execute`** - Request task execution
   - **CRITICAL:** Checks approval status before execution
   - Never executes without approval
   - Logs execution to database

5. **`taskrecorder.get_patterns`** - Get learned task patterns
   - Shows all observed patterns
   - Frequency, success rate, duration
   - Suggestion status

---

## 🔄 OPERATIONAL FLOW

```
User performs task
    ↓
TaskRecorder observes (via event listeners)
    ↓
Pattern updated (frequency, success rate)
    ↓
After 3+ observations + 70%+ success rate:
    ↓
Automation suggestion created
    ↓
Suggestion sent to user (via event)
    ↓
User reviews suggestion
    ↓
User approves OR rejects
    ↓
If approved: Task can be executed (but still requires approval per execution)
    ↓
Execution request checks approval status
    ↓
If approved: Execute and log
    ↓
If not approved: Reject with message
```

---

## 📊 DATABASE SCHEMA

### task_observations
- Records every task execution
- Includes: task type, signature, user, success, duration, context

### task_patterns
- Aggregated patterns from observations
- Includes: frequency, success rate, average duration, contexts

### automation_suggestions
- Suggestions awaiting approval
- Includes: confidence, observed count, suggested action, status

### task_executions
- Approved and executed tasks
- Includes: suggestion ID, params, approver, execution time

---

## 🚀 USAGE EXAMPLES

### Example 1: Observe Task (Automatic)
```typescript
// TaskRecorder automatically observes via event listeners
// No manual call needed - happens automatically when:
// - MCP tools are executed
// - Autonomous tasks are run
```

### Example 2: Get Suggestions
```typescript
// Via MCP
const suggestions = await mcp.send('backend', 'taskrecorder.get_suggestions', {});

// Returns:
{
  success: true,
  suggestions: [
    {
      id: 'sug-123',
      taskType: 'vidensarkiv.add',
      suggestedAction: 'Automate "vidensarkiv.add" task (observed 5 times with 100% success rate)',
      confidence: 1.0,
      observedCount: 5,
      estimatedBenefit: 'Saves ~150ms per execution',
      requiresApproval: true
    }
  ],
  count: 1
}
```

### Example 3: Approve Suggestion
```typescript
await mcp.send('backend', 'taskrecorder.approve', {
  suggestionId: 'sug-123'
});

// Returns:
{
  success: true,
  message: 'Automation suggestion approved',
  suggestionId: 'sug-123',
  approvedBy: 'user-123',
  note: 'Task can now be executed, but still requires approval for each execution'
}
```

### Example 4: Execute Task (With Approval Check)
```typescript
const result = await mcp.send('backend', 'taskrecorder.execute', {
  suggestionId: 'sug-123',
  taskSignature: 'sig-abc123',
  taskType: 'vidensarkiv.add',
  params: { content: 'test', metadata: {} }
});

// If approved:
{
  success: true,
  approved: true,
  executionId: 'exec-456',
  message: 'Task execution started (with approval)'
}

// If not approved:
{
  success: false,
  approved: false,
  message: 'Task execution requires approval. Please approve the suggestion first.'
}
```

---

## 🔒 SECURITY FEATURES

1. **Double Approval Check:**
   - Suggestion must be approved
   - Each execution still checks approval status

2. **Audit Trail:**
   - All approvals logged with userId and timestamp
   - All executions logged with approver info

3. **No Auto-Execution:**
   - `requiresApproval` is ALWAYS true for real tasks
   - Cannot be bypassed

4. **Event-Based Observation:**
   - Observes via event listeners (passive)
   - No interference with normal operations

---

## ⚙️ CONFIGURATION

**Thresholds:**
- `MIN_OBSERVATIONS_FOR_SUGGESTION = 3` - Suggest after 3 observations
- `MIN_CONFIDENCE_FOR_SUGGESTION = 0.7` - 70% success rate minimum

**Customizable:**
- Can adjust thresholds in TaskRecorder constructor
- Can modify suggestion criteria

---

## 📈 INTEGRATION POINTS

### Event Listeners
- `mcp.tool.executed` - Observes MCP tool executions
- `autonomous.task.executed` - Observes autonomous agent tasks

### Event Emitters
- `taskrecorder.suggestion.created` - New suggestion available
- `taskrecorder.suggestion.approved` - Suggestion approved
- `taskrecorder.execution.started` - Task execution started

### ProjectMemory Integration
- Logs all suggestions to ProjectMemory
- Tracks automation patterns

---

## ✅ TESTING

**Manual Test:**
1. Perform same task 3+ times
2. Check `taskrecorder.get_suggestions` - should see suggestion
3. Approve suggestion via `taskrecorder.approve`
4. Execute via `taskrecorder.execute` - should succeed
5. Try executing without approval - should fail

**Integration Test:**
1. Trigger MCP tools multiple times
2. Verify observations recorded
3. Verify patterns created
4. Verify suggestions generated
5. Test approval workflow

---

## 🎉 SUCCESS METRICS

- ✅ Task observation working
- ✅ Pattern learning functional
- ✅ Automation suggestions generated
- ✅ Approval workflow secure
- ✅ Execution requires approval
- ✅ Audit trail complete
- ✅ Never auto-executes without approval

---

**Implementation Date:** 2025-11-24  
**Status:** ✅ Complete and Secure  
**Security:** ✅ User approval ALWAYS required