chore(conductor): Initialize Phase 5 and curation tracks

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# Specification: Code Path & Data Pipeline Analysis (code_path_analysis_20260507)
## Overview
A deep architectural audit focused on mapping the "processing routes" and "data pipelines" of the Manual Slop codebase. This analysis will treat the program as a series of data-driven pipelines (similar to Ryan Fleury's model), identifying exactly how data flows through `./src` and `./simulation`.
## Scope
- **Core Codebase:** `./src`
- **Simulation Infrastructure:** `./simulation`
- **Granularity:** Both high-level module interactions and detailed function-to-function execution flows.
## Functional Requirements
1. **Pipeline Mapping:**
- Identify major execution "routes" (e.g., UI Event Loop, AI Tool-Call Loop, Context Aggregation Pipeline).
- Map these routes from entry point to terminal state.
2. **Data Responsibility Audit:**
- For every major path, define which data structures it owns, modifies, or depends upon.
- Identify state boundaries and potential "data leaks" or redundant processing.
3. **Simulation Pipeline Audit:**
- Fully map the lifecycle of a simulation: State Setup -> Agent Injection -> Execution Loop -> Verification -> Cleanup.
4. **Automated Extraction:**
- Utilize MCP tools and potentially custom `tree-sitter` scripts to verify call graphs and data dependencies.
## Acceptance Criteria
- [ ] Comprehensive `PIPELINE_ANALYSIS.md` report created in the root.
- [ ] Mermaid flowcharts documenting every major processing route.
- [ ] Data responsibility table for all mapped paths.
- [ ] Full mapping of the `./simulation` pipeline.