feat: scaffold tolkien v0 — local-LLM classifier wrapper + CLI + eval

Initial skeleton for the deterministic compound-AI pipeline that turns
`tolkien deploy <name>` into a valinor scaffold. v0 wires one classifier
(`db_kind`) end-to-end against the Ollama-on-radagast backend so we can
iterate prompts with confidence before adding the rest.

- pyproject.toml: uv project, Python 3.13, httpx/pydantic/typer/pyyaml.
- src/tolkien/llm.py: single-turn /api/chat wrapper. JSON-mode + temp 0 +
  30m keep-alive. Pydantic schema validation on parse.
- src/tolkien/cli.py: `tolkien classify db-kind --doc <file>` runs the
  classifier and prints JSON. `tolkien deploy <name>` is stubbed.
- src/tolkien/prompts/db_kind.md: tight system prompt with 1-shot example
  and explicit "return ONLY JSON" guard.
- src/tolkien/schemas.py: DbKindResult pydantic model.
- eval/cases/mealie.yml + run_eval.py: regression harness. Currently
  one case (mealie); failures print field-level diffs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

README.md

@@ -0,0 +1,49 @@
+# tolkien
+
+Local-LLM orchestrator that turns `tolkien deploy mealie` into a complete valinor
+GitOps scaffold (config.yaml, values.yaml, CNPG cluster, Vault secrets, Terraform
+stubs) ready for the operator to review and PR.
+
+## Architecture
+
+Compound-AI pipeline, not a ReAct loop. Each step in the deploy workflow is a
+single LLM call that produces structured JSON — the surrounding logic is plain
+Python. This shape works reliably on a CPU-served 7B model where a free-form
+agent loop would drift.
+
+```
+deploy <name>
+  ├── search.find_helm_chart()
+  ├── classify.has_chart(results)        — LLM, JSON
+  ├── fetch.app_docs(url)
+  ├── classify.db_kind(docs)             — LLM, JSON
+  ├── classify.needs_object_storage(docs)— LLM, JSON
+  ├── classify.secrets_vs_config(env)    — LLM, JSON
+  ├── classify.storage_class(docs)       — LLM, JSON
+  └── render.scaffold(facts)             — Jinja2 → ./out/<name>/
+```
+
+## Backend
+
+Ollama running on radagast (`http://radagast.jpnadas.xyz:11434`), serving
+Qwen2.5-Coder-7B-Instruct Q4_K_M. See valinor/`ansible/playbooks/radagast-setup.yml`
+for the host setup.
+
+## v0 scope
+
+- Single classifier (`db_kind`) wired end-to-end against the live model
+- CLI: `tolkien classify db-kind --doc <file>` prints JSON
+- Eval harness with one case (mealie)
+- Output to stdout / `./out/`; no git push, no FastAPI, no Redis
+
+v1 layers on FastAPI + Redis + a Gitea bot to push branches; v2 wires a Gitea
+webhook for issue-comment triggers.
+
+## Develop
+
+```bash
+uv sync
+uv run tolkien --help
+uv run pytest
+uv run ruff check .
+```