fix(context): merge overlay columns onto manifest columns by name (#94)

* fix(context): merge overlay columns onto manifest columns by name

composeOverlay was appending overlay columns to the manifest column list,
producing duplicate entries when dbt/metabase overlays declared a column
just to attach descriptions. The duplicates carried no `type`, so the
pydantic SourceDefinition rejected them at semantic-query time and broke
`ktx sl query` for every overlay-backed measure. Now overlay columns
match base columns by name (case-insensitive): same-name entries merge
onto the manifest (overlay fields win, type/role fall back to the base,
descriptions merge per source key) and only new names append.

* refactor(sl): split overlay columns from column_overrides and enforce TS/Python wire contract

Overlay sources now have two distinct collections: `columns:` for computed
columns (requiring `expr` + `type`) and `column_overrides:` for metadata
patches to inherited manifest columns. Composing or loading an overlay that
mixes the two — or references an unknown column — fails with a typed error.

Introduce `ResolvedSemanticLayerSource` / `resolvedSourceSchema` /
`toResolvedWire` as the strict shape sent to the Python engine, and add a
schema contract test that diffs Zod against the Pydantic JSON schema dumped
by `python -m semantic_layer dump-schema`. `SourceDefinition` is now
`extra="forbid"` on the Python side.

`loadAllSources` surfaces per-file load errors instead of swallowing them,
so validation/query paths can report manifest shard parse failures.

* fix(context): make scan description generation resilient and quiet

A transient sampleTable failure during ingest used to take out every
table in a connection: generateTableDescription returned a hardcoded
'Table not found' string into descriptions.ai, and KtxDescriptionGenerator
was constructed without a logger, so the failure left no trail anywhere.

- sampleTable / sampleColumn calls retry 3x with 200/400/800ms backoff,
  honouring KtxScanContext.signal via a new KtxAbortedError.
- On retry exhaustion or missing capability, table generation falls back
  to a metadata-only prompt built from column name / native type / comment
  / rawDescriptions. The column path follows the same rule -- call the
  LLM when any of samples or rawDescriptions are available; skip only
  when both are absent.
- Logger is now threaded from KtxScanContext into the generator. Failures
  emit structured KtxScanWarning entries (new description_fallback_used
  code, plus existing sampling_failed / enrichment_failed /
  connector_capability_missing). ktx scan groups warnings by code so a
  batch of identical failures collapses to one summary line plus sample.
- Returns null on failure instead of the 'Table not found' sentinel; the
  manifest writer's existing guard already skips empty descriptions, so
  schema YAML no longer carries misleading text. SCAN_MANAGED_DESCRIPTION_KEYS
  already strips stale 'ai' on merge, so existing YAML clears on next run.

Also suppress AI SDK v6 'system in messages' warning: pull system messages
out of KtxMessageBuilder.wrapSimple's output via a new splitKtxSystemMessages
helper and pass them top-level to generateText (preserves cacheControl
providerOptions on the SystemModelMessage). Agent-runner's local
splitSystemPromptMessages dedupes onto the shared helper.

* test(docs): align examples-docs assertions with revamped docs

PR #103 (setup/guide doc revamp) reworded several CLI examples and
connection labels; the assertions in scripts/examples-docs.test.mjs
still referenced the pre-revamp wording and were failing in CI on main.
Update the regexes to match the post-revamp content:

- drop the `--json` flag from the sl-query example expectation
- move the `Driver:` / `Status: ok` probe to the connection reference,
  which is where that output now lives (driver id is lowercase
  `postgres`, not the display name `PostgreSQL`)
- drop the obsolete `Install \`uv\`...` troubleshooting line
- accept `<connectionId>` everywhere; the docs no longer use the
  hyphenated `<connection-id>` form
- match the `warehouse` connection id used in the quickstart instead of
  the `postgres-warehouse` id only used in the README and setup ref

* fix(sl): skip TS/Python schema contract test when uv is unavailable

The TypeScript checks CI job does not install uv or Python, so the
module-level `execFileSync('uv', ...)` in schemas.contract.test.ts threw
ENOENT and failed the suite. Wrap the schema dump in a try/catch and
guard the describe block with `describe.skipIf` so the test skips in
environments without uv. Local dev and any CI job that has uv on PATH
still runs the cross-language contract assertion.

packages/context/src/ingest/adapters/metricflow/import-semantic-models.test.ts

@@ -38,7 +38,7 @@ describe('importMetricflowSemanticModels', () => {
     const scoped = {
       getManifestEntry: vi.fn().mockResolvedValue(null),
       isManifestBacked: vi.fn().mockResolvedValue(false),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockResolvedValue(null),
       writeSource: vi.fn().mockResolvedValue({ warnings: [] }),
     };
@@ -104,7 +104,7 @@ describe('importMetricflowSemanticModels', () => {
     const scoped = {
       getManifestEntry: vi.fn().mockResolvedValue(null),
       isManifestBacked: vi.fn().mockResolvedValue(false),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockImplementation((connectionId: string, sourceName: string) =>
         Promise.resolve(sourceName === 'orders' ? { name: 'orders' } : null),
       ),
@@ -139,7 +139,7 @@ describe('importMetricflowSemanticModels', () => {
     const scoped = {
       getManifestEntry: vi.fn().mockResolvedValue(null),
       isManifestBacked: vi.fn().mockResolvedValue(false),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockResolvedValue(null),
       writeSource: vi.fn().mockRejectedValueOnce(new Error('cannot write orders')).mockResolvedValue({ warnings: [] }),
     };
@@ -190,7 +190,7 @@ describe('importMetricflowSemanticModels', () => {
       isManifestBacked: vi.fn().mockImplementation(async (_connectionId: string, sourceName: string) => {
         return sourceName === 'orders';
       }),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockResolvedValue(null),
       writeSource: vi.fn().mockImplementation(async (_connectionId: string, source: (typeof written)[number]) => {
         written.push(source);
@@ -268,7 +268,7 @@ describe('importMetricflowSemanticModels', () => {
       isManifestBacked: vi.fn().mockImplementation(async (_connectionId: string, sourceName: string) => {
         return sourceName === 'orders';
       }),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockResolvedValue(null),
       writeSource: vi.fn().mockResolvedValue({ warnings: [] }),
     };
@@ -311,7 +311,7 @@ describe('importMetricflowSemanticModels', () => {
     const scoped = {
       getManifestEntry: vi.fn().mockResolvedValue(null),
       isManifestBacked: vi.fn().mockResolvedValue(false),
-      loadAllSources: vi.fn().mockResolvedValue([]),
+      loadAllSources: vi.fn().mockResolvedValue({ sources: [], loadErrors: [] }),
       loadSource: vi.fn().mockResolvedValue(null),
       writeSource: vi
         .fn()

packages/context/src/ingest/adapters/metricflow/import-semantic-models.ts

@@ -71,7 +71,7 @@ export async function importMetricflowSemanticModels(
   let crossModelSourcesCreated = 0;
 
   const preexistingSourceNames = new Set(
-    (await semanticLayerService.loadAllSources(input.connectionId)).map((source) => source.name),
+    (await semanticLayerService.loadAllSources(input.connectionId)).sources.map((source) => source.name),
   );
   const modelContexts: MetricflowSemanticModelImportContext[] = [];
   const sourceNameByModelRef = new Map<string, string>();