Feat v0.8.3 vector column type (#70)

Add vector(N) column type to db_tables manifests with three-tier
progressive enhancement: native pgvector on Postgres, JSONB fallback
without pgvector, TEXT fallback on SQLite. New db.query_similar()
Starlark builtin with dual-path dispatch.

- parseVectorDim validates 1..4096 dimensions
- mapColType gains hasPgvector parameter for tier selection
- HNSW index auto-created on pgvector backends
- starlarkToGoValue extended with list→JSON serialization
- cosineDistance helper for Go-side fallback computation
- ExtensionHandler gains SetCapabilities for install-time DDL
- Roadmap updated: v0.8.4 docs refresh + surface sizing fix

13 new tests (5 schema + 8 db module), all passing with -race.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

docs/STARLARK-REFERENCE.md

@@ -136,6 +136,33 @@ results = db.query_batch([
 # Each query spec supports: table (required), filters, order, limit, before, after, search_like
 ```
 
+#### Vector similarity search
+
+```python
+# Find rows with the most similar embeddings (cosine distance)
+rows = db.query_similar(
+    "documents",        # table name
+    "embedding",        # vector column name
+    vector=[0.1, 0.2, ...],  # query vector (list of floats)
+    limit=10,           # max results (default 10, max 100)
+    filters={"active": True},  # optional equality filters
+    metric="cosine",    # only "cosine" supported
+)
+# Returns rows ordered by ascending _distance (0.0 = identical, 1.0 = orthogonal)
+# Each row dict includes an injected "_distance" float key.
+```
+
+Vector columns are declared as `"vector(N)"` in the manifest `db_tables` block
+(N = dimension, 1–4096). Storage varies by backend:
+
+| Backend | Column type | Search |
+|---------|-------------|--------|
+| Postgres + pgvector | `vector(N)` with HNSW index | Native `<=>` operator |
+| Postgres (no pgvector) | `JSONB` | Go-side cosine computation |
+| SQLite | `TEXT` | Go-side cosine computation |
+
+Insert vectors as lists: `db.insert("docs", {"embedding": [0.1, 0.2, 0.3]})`.
+
 #### Write operations
 
 ```python