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conductor(track): Add task to remove hardcoded machine paths from mma_exec scripts

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Edward R. Gonzalez
2026-03-02 12:47:35 -05:00
parent dbe1647228
commit ff7f18b2ef
2 changed files with 10 additions and 4 deletions
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conductor/tracks/architecture_boundary_hardening_20260302/spec.md
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# Track Specification: Architecture Boundary Hardening
## Overview
The `manual_slop` project sandbox provides AI meta-tooling (`mma_exec.py`, `tool_call.py`) to orchestrate its own development. When AI agents added advanced AST tools (like `set_file_slice`) to `mcp_client.py` for meta-tooling, they failed to fully integrate them into the application's GUI, config, or HITL (Human-In-The-Loop) safety models. Additionally, meta-tooling scripts are bleeding tokens, and the internal application's state machine can deadlock.
The `manual_slop` project sandbox provides AI meta-tooling (`mma_exec.py`, `tool_call.py`) to orchestrate its own development. When AI agents added advanced AST tools (like `set_file_slice`) to `mcp_client.py` for meta-tooling, they failed to fully integrate them into the application's GUI, config, or HITL (Human-In-The-Loop) safety models. Additionally, meta-tooling scripts are bleeding tokens and rely on non-portable hardcoded machine paths, while the internal application's state machine can deadlock.
## Current State Audit
@@ -13,11 +13,16 @@ The `manual_slop` project sandbox provides AI meta-tooling (`mma_exec.py`, `tool
- Location: `scripts/mma_exec.py:101`.
- Issue: `UNFETTERED_MODULES` hardcodes `['mcp_client', 'project_manager', 'events', 'aggregate']`. If a worker targets a file that imports `mcp_client`, the script injects the full `mcp_client.py` (~450 lines) into the context instead of its skeleton, blowing out the token budget.
3. **DAG Engine Blocking Stalls (`dag_engine.py`)**:
3. **Portability Leak in Meta-Tooling Scripts**:
- Location: `scripts/mma_exec.py` and `scripts/claude_mma_exec.py`.
- Issue: Both scripts hardcode absolute external paths (`C:\projects\misc\setup_gemini.ps1` and `setup_claude.ps1`) to initialize the subprocess environment. This breaks repository portability.
4. **DAG Engine Blocking Stalls (`dag_engine.py`)**:
- Location: `dag_engine.py` -> `get_ready_tasks()`
- Issue: `get_ready_tasks` requires all dependencies to be explicitly `completed`. If a task is marked `blocked`, its dependents stay `todo` forever, causing an infinite stall.
## Desired State
- All tools in `mcp_client.py` are configurable in `manual_slop.toml` and `gui_2.py`. Mutating tools must route through the GUI approval callback.
- The `UNFETTERED_MODULES` list must be completely removed from `mma_exec.py`.
- Meta-tooling scripts rely on standard PATH or local relative config files, not hardcoded absolute external paths.
- The `dag_engine.py` must cascade `blocked` status to downstream tasks so the track halts cleanly.