Add API architecture documentation for Agent, Skill, and Tool pipeline

api/api.md

@@ -183,39 +183,3 @@ When the LLM responds with a tool call, the loop:
 
 4. Tool executes the request → ✅ Success
 ```
-
----
-
-## File Map
-
-```
-main.py                          # FastAPI app entry point, creates singletons
-├── core/
-│   ├── config.py                # .env loader, config constants
-│   └── llm.py                   # create_client() factory for OpenAI client
-├── api/
-│   ├── dependencies.py          # FastAPI Depends: get_llm_client()
-│   └── v1/
-│       └── chat.py              # APIRouter, endpoints, tool-calling loop
-├── agents/
-│   ├── __init__.py              # Agent dataclass, registry, load_all_agents()
-│   ├── naked.py                 # Agent: barebone LLM, no skills
-│   └── media_agent.py           # Agent: media assistant with Seerr skills
-└── skills/
-    ├── __init__.py              # Skill dataclass, ToolResult, registry, execution
-    ├── media_info.py            # Skill: base media assistant persona (prompt-only)
-    ├── seerr.py                 # Skill: Seerr API tools (7 tools, real API calls)
-    └── triage.py                # Skill: fallback for unsupported actions (prompt-only)
-```
-
-## Key Design Decisions
-
-1. **Full multi-turn history**: `req.messages` passes through unchanged. The LLM has access to its own previous responses (including `[tmdb:IDs]`). No external state management needed.
-
-2. **No deterministic pre-processing**: No affirmation detectors, reference resolvers, or hardcoded rules. The LLM interprets user intent naturally from full conversation context.
-
-3. **Agent selection via `model` field**: OpenWebUI sends `model` in the request. `_resolve_agent()` maps it to a registered agent. The `/v1/models` endpoint lists all agents as selectable models.
-
-4. **Skills = prompts + tools**: Skills inject prompt fragments AND optionally expose OpenAI function-calling tools. Prompt-only skills (like `triage`) just shape behavior. Tool-enabled skills (like `seerr`) let the LLM take real actions.
-
-5. **Singleton LLM client**: Created once in `main.py`, stored on `app.state.llm_client`, accessed via FastAPI `Depends(get_llm_client)`.