docs/technical/TASKRECORDER_IMPLEMENTATION.md

✅ TaskRecorder Implementation Complete

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

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🎯 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

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🔒 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

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📦 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

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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

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🔄 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

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📊 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)

// 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

// 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

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)

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

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📈 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

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✅ 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

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🎉 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

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