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@@ -28,6 +28,14 @@ This documentation suite provides comprehensive technical reference for the Manu
 | [NERV Theme](guide_nerv_theme.md) | "Black Void" palette with NERV orange/red/green/blue accents, zero-rounding geometry, CRT-style visual effects (scanlines, status flickering, alert animations), `theme_nerv.py` and `theme_nerv_fx.py` modules, FBO shader pipeline, configuration keys, performance cost, accessibility caveats |
 | [Workspace Profiles](guide_workspace_profiles.md) | Docking layouts and window visibility persistence, `WorkspaceProfile` schema with serialized `docking_layout` bytes, `WorkspaceManager` CRUD, scope inheritance (Global and Project), contextual auto-switch (experimental) binding profiles to MMA tier or task context, multi-monitor limitations |
 | [Command Palette](guide_command_palette.md) | Fuzzy command resolution with subsequence matching and scoring, async context preview worker to prevent UI hangs, "Everything" mode for cross-domain search (commands, files, symbols, history, settings), streaming results via thread-safe queue, cancellation on query change, 50+ built-in commands, user-defined commands via TOML |
+| [Testing](guide_testing.md) | 251 test files, 5 test categories (unit, integration, live_gui, perf, simulation), 7 conftest fixtures (`isolate_workspace`, `reset_paths`, `reset_ai_client`, `vlogger`, `kill_process_tree`, `mock_app`, `live_gui` session-scoped), Hook API testing pattern, Puppeteer pattern for MMA simulation, mock provider strategy, opt-in clean install test, opt-in docker test, coverage targets, anti-patterns (no arbitrary core mocking, artifact isolation to `tests/artifacts/`) |
+| [GUI Main](guide_gui_2.md) | `src/gui_2.py` reference: App class lifecycle, ~90 module-level render functions (UI Delegation Pattern), immgui immediate-mode rendering, Multi-Viewport docks, panel registry, command palette integration, ImGuiScope context managers, hot reload support, key bindings (Ctrl+Shift+P, Ctrl+Alt+R, Ctrl+Z/Y) |
+| [AI Client](guide_ai_client.md) | `src/ai_client.py` reference: multi-provider LLM singleton (5 providers: Gemini, Anthropic, DeepSeek, MiniMax, Gemini CLI), async dispatch with `asyncio.gather`, threading.local for source tier tagging, context caching (Anthropic ephemeral + Gemini explicit), system prompt assembly, error interception for Tier 4 QA |
+| [API Hooks](guide_api_hooks.md) | `src/api_hooks.py` + `src/api_hook_client.py` reference: HookServer on `127.0.0.1:8999`, ApiHookClient Python wrapper, 8+ endpoints (`/status`, `/api/gui`, `/api/ask`, `/api/mma_status`, `/api/performance`, `/api/comms`, `/api/diagnostics`), Remote Confirmation Protocol via `/api/ask` (synchronous blocking HITL), `custom_callback` action for invoking any registered App method |
+| [MCP Client](guide_mcp_client.md) | `src/mcp_client.py` reference: 45 native tools (File I/O, Python AST, C/C++ AST, Analysis, Network, Runtime, Beads), 3-layer security model (Allowlist Construction, Path Validation, Resolution Gate), `dispatch()`/`async_dispatch()` entry points, ExternalMCPManager for external MCP servers (Stdio + SSE), JSON-RPC 2.0 engine, public API, configuration |
+| [App Controller](guide_app_controller.md) | `src/app_controller.py` reference: headless orchestrator owning AppState and all subsystem managers (PresetManager, PersonaManager, ContextPresetManager, ToolPresetManager, ToolBiasEngine, RAGEngine, HistoryManager, WorkspaceManager, HookServer, HotReloader, PathManager), `_predefined_callbacks` and `_gettable_fields` registries for Hook API, SyncEventQueue bridge, preset/persona/context coordination, headless mode |
+| [MMA Engine](guide_multi_agent_conductor.md) | `src/multi_agent_conductor.py` + `src/dag_engine.py` reference: TrackDAG with cycle detection (iterative DFS) and topological sort (Kahn's variant), ExecutionEngine with Auto-Queue / Step Mode state machine, MultiAgentConductor with WorkerPool (configurable concurrency, default 4), mma_exec.py sub-agent invocation for Token Firewall, parse_plan_md utility, Beads mode delegation |
+| [Data Models](guide_models.md) | `src/models.py` reference: centralized data model registry using pydantic + dataclasses, model categories (Core, AI, Preset, Persona, Context, MMA, UI State, Logging, Hook, Workspace, RAG), `AGENT_TOOL_NAMES` canonical 45-tool list, `PROVIDERS` constant, `parse_plan_md` utility, validation patterns, SDM tags, serialization strategies (TOML, JSON-L) |
 
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