chore(conductor): Archive strategic overview and split into granular tracks
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# Track code_path_analysis_20260507 Context
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- [Specification](./spec.md)
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- [Implementation Plan](./plan.md)
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- [Metadata](./metadata.json)
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{
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"track_id": "code_path_analysis_20260507",
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"type": "chore",
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"status": "new",
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"created_at": "2026-05-07T15:00:00Z",
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"updated_at": "2026-05-07T15:00:00Z",
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"description": "Comprehensive analysis of major processing routes in ./src and ./simulation. Identify data pipelines and responsibilities."
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}
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# Implementation Plan: Code Path & Data Pipeline Analysis (code_path_analysis_20260507)
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## Phase 1: Structural Exploration & Tooling Setup
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- [x] Task: Initialize `PIPELINE_ANALYSIS.md` template.
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- [x] Task: Deploy `codebase_investigator` subagents to identify top-level entry points in `gui_2.py` and `simulation/`.
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- [x] Task: Verify usage of existing tree-sitter tools to generate initial call-graph skeletons for `./src`.
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- [x] Task: Conductor - User Manual Verification 'Phase 1' (Protocol in workflow.md)
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## Phase 2: Mapping Core Source Pipelines (`./src`)
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- [x] Task: Map the **Context Aggregation Pipeline** (`aggregate.py`, `models.py`).
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- [x] Task: Map the **AI Interaction Loop** (`ai_client.py`, `mcp_client.py`, `shell_runner.py`).
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- [x] Task: Map the **GUI Event & State Pipeline** (`gui_2.py`, `app_controller.py`).
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- [x] Task: Document data responsibilities and state boundaries for each route.
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- [x] Task: Conductor - User Manual Verification 'Phase 2' (Protocol in workflow.md)
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## Phase 3: Mapping Simulation Pipelines (`./simulation`)
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- [x] Task: Map the **Simulation Lifecycle** (`sim_base.py`, `sim_context.py`, `workflow_sim.py`).
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- [x] Task: Analyze data flow between `sim_ai_settings.py` and the execution engine.
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- [x] Task: Document the "Verification & Checkpointing" route in simulations.
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- [x] Task: Conductor - User Manual Verification 'Phase 3' (Protocol in workflow.md)
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## Phase 4: Synthesis & Reporting
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- [x] Task: Consolidate all findings into Mermaid diagrams within `PIPELINE_ANALYSIS.md`.
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- [x] Task: Identify specific "Curation Targets" (redundancies, style violations) for the next track.
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- [x] Task: Final review and hand-off to Track 2 (Codebase Curation).
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- [x] Task: Conductor - User Manual Verification 'Phase 4' (Protocol in workflow.md)
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# Specification: Code Path & Data Pipeline Analysis (code_path_analysis_20260507)
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## Overview
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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`.
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## Scope
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- **Core Codebase:** `./src`
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- **Simulation Infrastructure:** `./simulation`
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- **Granularity:** Both high-level module interactions and detailed function-to-function execution flows.
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## Functional Requirements
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1. **Pipeline Mapping:**
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- Identify major execution "routes" (e.g., UI Event Loop, AI Tool-Call Loop, Context Aggregation Pipeline).
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- Map these routes from entry point to terminal state.
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2. **Data Responsibility Audit:**
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- For every major path, define which data structures it owns, modifies, or depends upon.
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- Identify state boundaries and potential "data leaks" or redundant processing.
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3. **Simulation Pipeline Audit:**
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- Fully map the lifecycle of a simulation: State Setup -> Agent Injection -> Execution Loop -> Verification -> Cleanup.
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4. **Automated Extraction:**
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- Utilize MCP tools and potentially custom `tree-sitter` scripts to verify call graphs and data dependencies.
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## Acceptance Criteria
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- [ ] Comprehensive `PIPELINE_ANALYSIS.md` report created in the root.
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- [ ] Mermaid flowcharts documenting every major processing route.
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- [ ] Data responsibility table for all mapped paths.
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- [ ] Full mapping of the `./simulation` pipeline.
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