docs: replace CLAUDE.md with AGENTS.md and add frontend details

AGENTS.md

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+# AGENTS.md
+
+This file provides guidance to AI coding agents when working with code in this repository.
+
+## Repository Structure
+
+This is a monorepo with **backend** and **frontend** directories.
+
+## Commands
+
+Run the backend from the `backend/` directory:
+
+```bash
+# Backend
+cd backend && uv run python main.py
+
+# Linting / formatting
+cd backend && uv run ruff check .
+cd backend && uv run black .
+cd backend && uv run isort .
+```
+
+Run the frontend from the `frontend/` directory:
+
+```bash
+# Frontend
+cd frontend && pnpm dev
+
+# Type checking / linting / formatting
+cd frontend && pnpm check
+cd frontend && pnpm lint
+cd frontend && pnpm format
+```
+
+No test suite exists yet (backend has some test files but they're not integrated into CI).
+
+## Architecture
+
+**innercontext** collects personal health and skincare data and exposes it via MCP to an LLM agent.
+
+**Backend Stack:** Python 3.12, SQLModel (0.0.37) + SQLAlchemy, Pydantic v2, FastAPI, PostgreSQL (psycopg3).
+
+**Frontend Stack:** SvelteKit 5, Tailwind CSS v4, bits-ui, inlang/paraglide (i18n), svelte-dnd-action.
+
+### MCP Server (`backend/innercontext/mcp_server.py`)
+
+### Models (`backend/innercontext/models/`)
+
+| File | Tables |
+|------|--------|
+| `product.py` | `products`, `product_inventory` |
+| `health.py` | `medication_entries`, `medication_usages`, `lab_results` |
+| `routine.py` | `routines`, `routine_steps` |
+| `skincare.py` | `skin_condition_snapshots` |
+
+**`Product`** is the core model. JSON columns store `inci` (list), `actives` (list of `ActiveIngredient`), `recommended_for`, `targets`, `incompatible_with`, `synergizes_with`, `context_rules`, and `product_effect_profile`. The `to_llm_context()` method returns a token-optimised dict for MCP.
+
+**`ProductInventory`** tracks physical packages (opened status, expiry, remaining weight). One product → many inventory entries.
+
+**`Routine` / `RoutineStep`** record daily AM/PM skincare sessions. A step references either a `Product` or a free-text `action` (e.g. shaving).
+
+**`SkinConditionSnapshot`** is a weekly LLM-filled record (skin state, metrics 1–5, active concerns).
+
+### Key Conventions
+
+- All `table=True` models use `Column(DateTime(timezone=True), onupdate=utc_now)` for `updated_at` via raw SQLAlchemy column — do not use plain `Field(default_factory=...)` for auto-update.
+- List/complex fields stored as JSON use `sa_column=Column(JSON, nullable=...)` pattern (DB-agnostic; not JSONB).
+- `model_validator(mode="after")` **does not fire** on `table=True` SQLModel instances (SQLModel 0.0.37 + Pydantic v2 bug). Validators in `Product` are present for documentation but are unreliable at construction time.
+- `backend/skincare.yaml` is a legacy notes file — ignore it, it is not part of the data model and will not be imported.
+- `_ev()` helper in `product.py` normalises enum values when fields may be raw dicts (as returned from DB) or Python enum instances.