# TGI / TLM System Audit (March 2026)

## 1. Documentation Gaps (Genuine Gaps)
- **API Completeness**: 556 classes/methods lack docstrings in `docs/API.md`. High-impact modules like `algebraic.py` and `aimo_3_gateway.py` are largely undocumented.
- **Dependency Map**: No `requirements.txt` or `pyproject.toml` exists, making environment setup brittle (identified during the audit).
- **Architecture Visualization**: No diagram or formal specification for the Five-Core interaction, though `tgi_system_demo.py` provides a functional example.

## 2. Structural Weaknesses
- **Unit Testing**: Major `research/` modules (`tlm.py`, `knowledge_mapper.py`, `agentic_bridge.py`) lack unit tests. The system relies heavily on high-level demos and integration tests.
- **Error Handling**: `ActionMapper` and `AgenticBridge` use deterministic mappings without robust fallbacks or error-correction for "out-of-manifold" inputs.
- **Agentic Autonomy**: While the "Action Engine" can generate plans, the actual execution (looping back result to TGI, handling retries) is not implemented.
- **Mobile Packaging**: The `android/` directory contains skeletons, but no automated build or CI/CD for the APK exists yet.

## 3. High-Impact Improvements
- **TLM-Based Intent Lifting**: Replace MD5 hashing in `ActionMapper.resolve_intent` with a grounded TLM lifting to ensure semantic alignment.
- **Hardware-Responsive Manifolds**: Implement the dynamic $m$ resizing based on `HardwareMapper` telemetry as proposed in Phase 7.
- **Closed-Loop Autonomy**: Implement the "Agentic Action Engine" executor that can actually call MCP tools and return results to the TGI core.
- **Symbolic Solver Expansion**: Integrate the `AIMOReasoningEngine` more deeply into the `TGIAgent.query` path for complex multi-step math problems.

## 4. Prioritized Next Phase (Phase 8: Closed-Loop Sovereign Autonomy)
1. **Infrastructure**: Create `requirements.txt` and a basic unit test suite for core `research/` modules.
2. **Refinement**: Implement full TLM-based intent lifting in `ActionMapper`.
3. **Execution**: Build the `ActionExecutor` to bridge the gap between "Plan Generation" and "Autonomous Task Completion".
4. **Resilience**: Add Law-based guardrails to the `AgenticBridge` to prevent "Topological Drift" during multi-step plans.

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*Audit performed by Jules — March 2026*