# Specification: MMA Utilization Refinement

## Overview
Refine the Multi-Model Architecture (MMA) implementation within the Conductor framework to ensure clear role segregation, proper tool permissions, and improved observability for sub-agents.

## Goals
- Enforce Tier 1 as the track creator and Tier 2 as the track executor.
- Restore and fix segregated skills (`mma-tier1` through `mma-tier4`).
- Provide Tier 3 & 4 with direct file I/O tools to reduce Tier 2 context bloat.
- Implement AST-based "Skeleton Views" for Tier 3 context injection.
- Create a non-polluting verbose log/feed for sub-agent operations.
- Remove "Context Amnesia" from Tier 2 while maintaining it for Tiers 3 & 4.

## Functional Requirements
1. **Skill Refinement:**
   - Update `mma-tier1-orchestrator` to focus on `/conductor:setup` and `/conductor:newTrack`.
   - Update `mma-tier2-tech-lead` to manage `/conductor:implement`. It must maintain persistent context for the duration of a track session (no amnesia).
   - Update `mma-tier3-worker` and `mma-tier4-qa` to be stateless (Context Amnesia) but equipped with `read_file`, `write_file`, and codebase exploration tools.
2. **AST Extraction (Skeleton Views):**
   - Enhance `mcp_client.py` (or a dedicated utility) to generate Python skeletons (signatures and docstrings) using `tree-sitter`.
   - Update `mma_exec.py` to utilize these skeletons for modules NOT being actively worked on by Tier 3.
3. **Observability:**
   - Ensure sub-agent reasoning and tool calls are logged to a dedicated log file (e.g., `logs/mma_subagents.log`) or separate shell to avoid polluting the main session history.
4. **Workflow Update:**
   - Update `conductor/workflow.md` to reflect the new tier responsibilities and tool access rules.

## Acceptance Criteria
- [ ] Tier 1 can successfully initialize a track.
- [ ] Tier 2 can delegate a coding task to Tier 3.
- [ ] Tier 3 receives a "Skeleton View" of relevant dependencies instead of full files.
- [ ] Tier 3 can write files back to the project.
- [ ] Tier 4 can analyze logs and provide summaries.
- [ ] Sub-agent verbose output is captured in a dedicated log.
- [ ] Tier 2 context remains focused on the high-level plan, not implementation details.