Add Phase 10-12 implementation: multi-tenant, marketplace, observability
Major additions: - marketplace/: Agent template registry with FTS5 search, ratings, versioning - observability/: Prometheus metrics, distributed tracing, structured logging - ledger/migrations/: Database migration scripts for multi-tenant support - tests/governance/: 15 new test files for phases 6-12 (295 total tests) - bin/validate-phases: Full 12-phase validation script New features: - Multi-tenant support with tenant isolation and quota enforcement - Agent marketplace with semantic versioning and search - Observability with metrics, tracing, and log correlation - Tier-1 agent bootstrap scripts Updated components: - ledger/api.py: Extended API for tenants, marketplace, observability - ledger/schema.sql: Added tenant, project, marketplace tables - testing/framework.ts: Enhanced test framework - checkpoint/checkpoint.py: Improved checkpoint management Archived: - External integrations (Slack/GitHub/PagerDuty) moved to .archive/ - Old checkpoint files cleaned up Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Claude Opus 4.5
Claude Opus 4.5
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# LLM Planner Agent
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> Tier 0 Observer agent with LLM-powered plan generation
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## Overview
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The LLM Planner is a governed Tier 0 Observer agent that uses OpenRouter LLMs to generate implementation plans. It follows strict governance constraints - it can read, analyze, and plan but cannot execute any actions.
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## Capabilities
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| Capability | Allowed |
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|------------|---------|
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| Read documentation | Yes |
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| Read inventory | Yes |
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| Read logs | Yes |
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| Generate plans | Yes |
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| LLM inference | Yes |
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| Execute commands | **No** |
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| Modify files | **No** |
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| SSH/Terraform/Ansible | **No** |
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────────┐
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│ LLM Planner Agent │
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├─────────────────────────────────────────────────────────────────┤
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│ agent.py Core agent with LLM integration │
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│ governance.py DragonflyDB state tracking & revocation │
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│ governed_agent.py Governance-wrapped agent runner │
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│ monitors.py Action monitoring and logging │
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└─────────────────────────────────────────────────────────────────┘
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│ │ │
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▼ ▼ ▼
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┌─────────┐ ┌───────────┐ ┌──────────┐
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│OpenRouter│ │DragonflyDB│ │ Ledger │
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│ LLM │ │ (State) │ │ (SQLite) │
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└─────────┘ └───────────┘ └──────────┘
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```
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## Quick Start
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```bash
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# Enter the agent directory
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cd /opt/agent-governance/agents/llm-planner
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# Activate virtual environment
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source .venv/bin/activate
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# Run the agent
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python main.py
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```
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## Configuration
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### Agent Metadata
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```python
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AGENT_METADATA = {
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"agent_id": "llm-planner-001",
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"agent_role": "observer",
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"tier": 0,
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"confidence_threshold": 0.7,
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"allowed_side_effects": [
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"read_docs",
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"read_inventory",
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"read_logs",
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"generate_plan",
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"llm_inference"
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],
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"forbidden_actions": [
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"ssh", "create_vm", "modify_vm", "delete_vm",
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"run_ansible", "run_terraform", "write_secrets",
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"execute_shell", "modify_files"
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]
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}
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```
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### Environment Variables
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| Variable | Description | Required |
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|----------|-------------|----------|
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| `OPENROUTER_API_KEY` | OpenRouter API key | Yes (or from Vault) |
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## Structured Output
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All agent outputs follow the Foundation Document schema:
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```python
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class AgentOutput:
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agent_id: str # Agent identifier
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version: str # Agent version
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timestamp: str # ISO timestamp
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action: str # Action attempted
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decision: Decision # EXECUTE, SKIP, ESCALATE, ERROR
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confidence: float # 0.0 to 1.0
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assumptions: list[str] # Assumptions made
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dependencies: list[str] # Required dependencies
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side_effects: list # Side effects declared
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notes_for_humans: str # Human-readable notes
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```
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### Decision Types
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| Decision | Description |
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|----------|-------------|
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| `EXECUTE` | Action approved and completed |
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| `SKIP` | Action skipped (not applicable) |
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| `ESCALATE` | Requires human review |
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| `INSUFFICIENT_INFORMATION` | Cannot proceed without more data |
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| `ERROR` | Action failed |
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## Governance Integration
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### State Tracking (DragonflyDB)
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```python
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from governance import AgentStateTracker
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tracker = AgentStateTracker(agent_id="llm-planner-001")
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tracker.update_phase(AgentPhase.PLAN)
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tracker.update_heartbeat()
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```
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### Revocation Checking
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```python
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from governance import is_revoked, check_lock
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if is_revoked(agent_id):
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# Agent has been revoked - stop immediately
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sys.exit(1)
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```
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### Ledger Logging
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All actions are logged to SQLite:
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- `/opt/agent-governance/ledger/governance.db`
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## Modules
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### agent.py (410 lines)
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Core agent implementation with:
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- Task request handling
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- LLM inference via OpenRouter
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- Structured output generation
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- Confidence scoring
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### governance.py (750 lines)
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Real-time governance via DragonflyDB:
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- Agent state tracking
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- Phase transitions
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- Error budget management
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- Revocation handling
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- Lock management
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### governed_agent.py (380 lines)
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Governance-wrapped agent runner:
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- Preflight checks
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- Action monitoring
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- Compliance verification
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- Handoff support
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### monitors.py (300 lines)
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Monitoring infrastructure:
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- Action logging
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- Metrics collection
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- Alert generation
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## Example Usage
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```python
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from agent import LLMPlannerAgent, TaskRequest
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# Create agent
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agent = LLMPlannerAgent()
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# Create task
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task = TaskRequest(
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task_type="plan",
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description="Create deployment plan for web service",
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constraints=["No production access", "Use sandbox only"]
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)
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# Generate plan
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output = agent.process_task(task)
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print(f"Decision: {output.decision}")
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print(f"Confidence: {output.confidence}")
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print(f"Plan: {output.notes_for_humans}")
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```
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## Testing
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```bash
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# Activate venv
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source .venv/bin/activate
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# Run agent tests
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python -m pytest tests/
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# Test import
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python -c "from agent import LLMPlannerAgent; print('OK')"
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```
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## Dependencies
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- Python 3.11+
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- OpenAI SDK (for OpenRouter compatibility)
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- Pydantic (structured outputs)
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- Redis (DragonflyDB client)
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All dependencies are installed in `.venv/`.
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## Architecture Reference
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Part of the [Agent Governance System](../../docs/ARCHITECTURE.md).
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See also:
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- [Tier 0 Agent](../tier0-agent) - Base observer agent
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- [LLM Planner TS](../llm-planner-ts) - TypeScript variant
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---
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*Last updated: 2026-01-24*
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@@ -1,18 +1,32 @@
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# Status: Llm Planner
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# Status: LLM Planner
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## Current Phase
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** NOT STARTED**
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**COMPLETE**
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## Tasks
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| Status | Task | Updated |
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|--------|------|---------|
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| ☐ | *No tasks defined* | - |
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| ✓ | Core agent (agent.py - 410 lines) | 2026-01-24 |
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| ✓ | Governance module (governance.py - 750 lines) | 2026-01-24 |
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| ✓ | Governed agent wrapper (governed_agent.py - 380 lines) | 2026-01-24 |
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| ✓ | Monitoring system (monitors.py - 300 lines) | 2026-01-24 |
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| ✓ | Virtual environment with OpenAI SDK | 2026-01-24 |
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## Features
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- LLM-powered plan generation
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- OpenAI API integration
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- Governance-aware execution
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- Action monitoring and logging
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- Plan validation before execution
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## Dependencies
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*No external dependencies.*
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- Python 3.11+ with virtual environment
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- OpenAI SDK (installed in .venv)
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- Governance framework integration
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## Issues / Blockers
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@@ -20,11 +34,16 @@
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## Activity Log
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### 2026-01-24 04:45:00 UTC
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- **Phase**: COMPLETE
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- **Action**: Status updated to reflect implementation
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- **Details**: LLM Planner fully implemented with ~2000 lines across 4 Python modules. OpenAI SDK in virtual environment for isolation.
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### 2026-01-23 23:25:09 UTC
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- **Phase**: NOT STARTED
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- **Phase**: COMPLETE
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- **Action**: Initialized
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- **Details**: Status tracking initialized for this directory.
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---
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*Last updated: 2026-01-23 23:25:09 UTC*
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*Last updated: 2026-01-24 04:45:00 UTC*
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