adjustments

conductor/workflow.md

@@ -34,8 +34,6 @@ with open('file.py', 'w', encoding='utf-8', newline='') as f:
 
 ## Guiding Principles
 
-## Guiding Principles
-
 1. **The Plan is the Source of Truth:** All work must be tracked in `plan.md`
 2. **The Tech Stack is Deliberate:** Changes to the tech stack must be documented in `tech-stack.md` *before* implementation
 3. **Test-Driven Development:** Write unit tests before implementing functionality
@@ -360,93 +358,32 @@ A task is complete when:
 8. Changes committed with proper message
 9. Git note with task summary attached to the commit
 
-## Emergency Procedures
-
-### Critical Bug in Production
-
-1. Create hotfix branch from main
-2. Write failing test for bug
-3. Implement minimal fix
-4. Test thoroughly including mobile
-5. Deploy immediately
-6. Document in plan.md
-
-### Data Loss
-
-1. Stop all write operations
-2. Restore from latest backup
-3. Verify data integrity
-4. Document incident
-5. Update backup procedures
-
-### Security Breach
-
-1. Rotate all secrets immediately
-2. Review access logs
-3. Patch vulnerability
-4. Notify affected users (if any)
-5. Document and update security procedures
-
-## Deployment Workflow
-
-### Pre-Deployment Checklist
-
-- [ ] All tests passing
-- [ ] Coverage >80%
-- [ ] No linting errors
-- [ ] Mobile testing complete
-- [ ] Environment variables configured
-- [ ] Database migrations ready
-- [ ] Backup created
-
-### Deployment Steps
-
-1. Merge feature branch to main
-2. Tag release with version
-3. Push to deployment service
-4. Run database migrations
-5. Verify deployment
-6. Test critical paths
-7. Monitor for errors
-
-### Post-Deployment
-
-1. Monitor analytics
-2. Check error logs
-3. Gather user feedback
-4. Plan next iteration
-
-## Continuous Improvement
-
-- Review workflow weekly
-- Update based on pain points
-- Document lessons learned
-- Optimize for user happiness
-- Keep things simple and maintainable
-
 ## Conductor Token Firewalling & Model Switching Strategy
 
 To emulate the 4-Tier MMA Architecture within the standard Conductor extension without requiring a custom fork, adhere to these strict workflow policies:
 
 ### 1. Active Model Switching (Simulating the 4 Tiers)
+
 - **Mandatory Skill Activation:** As the very first step of any MMA-driven process, including track initialization and implementation phases, the agent MUST activate the `mma-orchestrator` skill (`activate_skill mma-orchestrator`). This is crucial for enforcing the 4-Tier token firewall.
-- **The MMA Bridge (`mma_exec.py`):** All tiered delegation is routed through `python scripts/mma_exec.py`. This script acts as the primary bridge, managing model selection, context injection, and logging.
+- **The MMA Bridge (`mma_exec.py`):** All tiered delegation is routed through `uv python scripts/mma_exec.py`. This script acts as the primary bridge, managing model selection, context injection, and logging.
 - **Model Tiers:**
     - **Tier 1 (Strategic/Orchestration):** `gemini-3.1-pro-preview`. Focused on product alignment, setup (`/conductor:setup`), and track initialization (`/conductor:newTrack`).
     - **Tier 2 (Architectural/Tech Lead):** `gemini-3-flash-preview`. Focused on architectural design and track execution (`/conductor:implement`). **Note:** Tier 2 maintains persistent memory throughout a track's implementation.
     - **Tier 3 (Execution/Worker):** `gemini-2.5-flash-lite`. Used for surgical code implementation and test generation. Operates statelessly (Context Amnesia) but has access to file I/O tools.
     - **Tier 4 (Utility/QA):** `gemini-2.5-flash-lite`. Used for log summarization and error analysis. Operates statelessly (Context Amnesia) but has access to diagnostic tools.
 - **Tiered Delegation Protocol:**
-    - **Tier 3 Worker:** `python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`
-    - **Tier 4 QA Agent:** `python scripts/mma_exec.py --role tier4-qa "[PROMPT]"`
+    - **Tier 3 Worker:** `uv run python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`
+    - **Tier 4 QA Agent:** `uv run python scripts/mma_exec.py --role tier4-qa "[PROMPT]"`
 - **Observability:** All hierarchical interactions are recorded in `logs/mma_delegation.log` and detailed sub-agent logs are saved to `logs/agents/`.
 
 ### 2. Context Management and Token Firewalling
+
 - **Context Amnesia (Tiers 3 & 4):** `mma_exec.py` enforces "Context Amnesia" by executing sub-agents in a stateless manner. Each call starts with a clean slate, receiving only the strictly necessary documents and prompts.
 - **Persistent Memory (Tier 2):** The Tier 2 Tech Lead does NOT use Context Amnesia during track implementation to ensure continuity of technical strategy.
 - **AST Skeleton Views:** For Tier 3 implementation, `mma_exec.py` automatically generates "AST Skeleton Views" of project dependencies. This provides the worker model with the interface-level structure (function signatures, docstrings) of imported modules without the full source code, maximizing the signal-to-noise ratio in the context window.
 
 ### 3. Phase Checkpoints (The Final Defense)
+
 - The **Phase Completion Verification and Checkpointing Protocol** is the project's primary defense against token bloat.
 - When a Phase is marked complete and a checkpoint commit is created, the AI Agent must actively interpret this as a **"Context Wipe"** signal. It should summarize the outcome in its git notes and move forward treating the checkpoint as absolute truth, deliberately dropping earlier conversational history.
 - **MMA Phase Memory Wipe:** After completing a major Phase, use the Tier 1/2 Orchestrator's perspective to consolidate state into Git Notes and then disregard previous trial-and-error histories.