fix: surface silent failures in SL, wiki, and embedding wiring (#195)

* fix: surface silent failures in SL, wiki, and embedding wiring

- require non-empty `vertex.location` in the project schema instead of defaulting
  to an empty string with a description that promised SDK fallback the resolver
  never honored
- log YAML parse failures from `SemanticLayerService.loadSource` and
  `KnowledgeWikiService.readPage` so corrupted overlays aren't silently treated
  as "does not exist" by ingest/agent tools
- push directory-listing errors in `loadAllSources` and `listPageKeys` into the
  load-error / log path instead of returning empty success
- accept an `embeddingProvider` in `createLocalProjectMemoryIngest` and plumb the
  resolved CLI provider through `mcp-server-factory`; warn in both the memory
  and bundle runtimes when they fall back to `NoopEmbeddingPort` while the
  project config requests an active embedding backend
- clarify `embeddings.dimensions` description as a placeholder valid only with
  `backend: none`, and tighten the sentence-transformers `base_url` description
  to call out that managed-daemon resolution is CLI-only

* test: improve PR coverage

packages/cli/src/mcp-server-factory.test.ts

@@ -0,0 +1,193 @@
+import { createDefaultKtxMcpServer, createLocalProjectMcpContextPorts } from '@ktx/context/mcp';
+import { createLocalProjectMemoryIngest } from '@ktx/context/memory';
+import { beforeEach, describe, expect, it, vi } from 'vitest';
+import { resolveProjectEmbeddingProvider } from './embedding-resolution.js';
+import { createKtxCliScanConnector } from './local-scan-connectors.js';
+import { createKtxMcpServerFactory } from './mcp-server-factory.js';
+
+type FakeEmbeddingProvider = {
+  maxBatchSize: number;
+  embed(text: string): Promise<number[]>;
+  embedMany(texts: string[]): Promise<number[][]>;
+};
+
+const mocks = vi.hoisted(() => ({
+  queryExecutor: { execute: vi.fn() },
+  semanticLayerCompute: { validateSources: vi.fn(), generateSources: vi.fn(), query: vi.fn() },
+  sqlAnalysis: { analyzeForFingerprint: vi.fn(), analyzeBatch: vi.fn(), validateReadOnly: vi.fn() },
+  memoryIngest: { ingest: vi.fn(), status: vi.fn(), waitForRun: vi.fn() },
+}));
+
+vi.mock('@ktx/context', () => ({
+  KtxIngestEmbeddingPortAdapter: class {
+    readonly maxBatchSize: number;
+
+    constructor(private readonly provider: FakeEmbeddingProvider) {
+      this.maxBatchSize = provider.maxBatchSize;
+    }
+
+    computeEmbedding(text: string): Promise<number[]> {
+      return this.provider.embed(text);
+    }
+
+    computeEmbeddingsBulk(texts: string[]): Promise<number[][]> {
+      return this.provider.embedMany(texts);
+    }
+  },
+}));
+
+vi.mock('@ktx/context/mcp', () => ({
+  createDefaultKtxMcpServer: vi.fn(() => ({ kind: 'mcp-server' })),
+  createLocalProjectMcpContextPorts: vi.fn(() => ({ context_tool: { name: 'context_tool' } })),
+}));
+
+vi.mock('@ktx/context/memory', () => ({
+  createLocalProjectMemoryIngest: vi.fn(() => mocks.memoryIngest),
+}));
+
+vi.mock('./embedding-resolution.js', () => ({
+  resolveProjectEmbeddingProvider: vi.fn(),
+}));
+
+vi.mock('./ingest-query-executor.js', () => ({
+  createKtxCliIngestQueryExecutor: vi.fn(() => mocks.queryExecutor),
+}));
+
+vi.mock('./local-scan-connectors.js', () => ({
+  createKtxCliScanConnector: vi.fn(() => ({ source: 'fake-scan-connector' })),
+}));
+
+vi.mock('./managed-python-command.js', () => ({
+  createManagedPythonSemanticLayerComputePort: vi.fn(async () => mocks.semanticLayerCompute),
+}));
+
+vi.mock('./managed-python-http.js', () => ({
+  createManagedDaemonSqlAnalysisPort: vi.fn(() => mocks.sqlAnalysis),
+}));
+
+const project = {
+  projectDir: '/work/project',
+  configPath: '/work/project/ktx.yaml',
+  config: {},
+  coreConfig: {},
+  git: {},
+  fileStore: {},
+};
+
+const io = {
+  stdout: { write: vi.fn() },
+  stderr: { write: vi.fn() },
+};
+
+describe('createKtxMcpServerFactory', () => {
+  beforeEach(() => {
+    vi.clearAllMocks();
+  });
+
+  it('passes a resolved embedding provider to MCP context ports and memory ingest', async () => {
+    const provider = {
+      maxBatchSize: 4,
+      embed: vi.fn(async () => [0.2, 0.4]),
+      embedMany: vi.fn(async () => [[0.2, 0.4]]),
+    };
+    vi.mocked(resolveProjectEmbeddingProvider).mockResolvedValue({ kind: 'configured', provider } as never);
+
+    const factory = await createKtxMcpServerFactory({
+      project: project as never,
+      projectDir: project.projectDir,
+      cliVersion: '0.5.0',
+      io,
+    });
+
+    const contextOptions = vi.mocked(createLocalProjectMcpContextPorts).mock.calls[0][1] as {
+      embeddingService: {
+        computeEmbedding(text: string): Promise<number[]>;
+        computeEmbeddingsBulk(texts: string[]): Promise<number[][]>;
+      };
+      queryExecutor: unknown;
+      semanticLayerCompute: unknown;
+      sqlAnalysis: unknown;
+      localScan: {
+        createConnector(connectionId: string): Promise<unknown>;
+      };
+    };
+    await expect(contextOptions.embeddingService.computeEmbedding('gross revenue')).resolves.toEqual([0.2, 0.4]);
+    await expect(contextOptions.embeddingService.computeEmbeddingsBulk(['gross revenue'])).resolves.toEqual([[0.2, 0.4]]);
+    await expect(contextOptions.localScan.createConnector('warehouse')).resolves.toEqual({
+      source: 'fake-scan-connector',
+    });
+
+    expect(provider.embed).toHaveBeenCalledWith('gross revenue');
+    expect(provider.embedMany).toHaveBeenCalledWith(['gross revenue']);
+    expect(createKtxCliScanConnector).toHaveBeenCalledWith(project, 'warehouse');
+    expect(contextOptions).toMatchObject({
+      queryExecutor: mocks.queryExecutor,
+      semanticLayerCompute: mocks.semanticLayerCompute,
+      sqlAnalysis: mocks.sqlAnalysis,
+    });
+    expect(createLocalProjectMemoryIngest).toHaveBeenCalledWith(
+      project,
+      expect.objectContaining({
+        embeddingProvider: provider,
+        queryExecutor: mocks.queryExecutor,
+        semanticLayerCompute: mocks.semanticLayerCompute,
+      }),
+    );
+
+    expect(factory()).toEqual({ kind: 'mcp-server' });
+    expect(createDefaultKtxMcpServer).toHaveBeenCalledWith(
+      expect.objectContaining({
+        contextTools: expect.objectContaining({
+          context_tool: { name: 'context_tool' },
+          memoryIngest: mocks.memoryIngest,
+        }),
+      }),
+    );
+  });
+
+  it('uses null embedding ports when no configured provider is available', async () => {
+    vi.mocked(resolveProjectEmbeddingProvider).mockResolvedValue({ kind: 'managed-unavailable' } as never);
+
+    await createKtxMcpServerFactory({
+      project: project as never,
+      projectDir: project.projectDir,
+      cliVersion: '0.5.0',
+      io,
+    });
+
+    expect(vi.mocked(createLocalProjectMcpContextPorts).mock.calls[0][1]).toMatchObject({
+      embeddingService: null,
+    });
+    expect(createLocalProjectMemoryIngest).toHaveBeenCalledWith(
+      project,
+      expect.objectContaining({
+        embeddingProvider: null,
+      }),
+    );
+  });
+
+  it('omits memory ingest and logs when memory ingest construction fails', async () => {
+    vi.mocked(resolveProjectEmbeddingProvider).mockResolvedValue({ kind: 'disabled' } as never);
+    vi.mocked(createLocalProjectMemoryIngest).mockImplementationOnce(() => {
+      throw new Error('missing local memory prerequisites');
+    });
+
+    const factory = await createKtxMcpServerFactory({
+      project: project as never,
+      projectDir: project.projectDir,
+      cliVersion: '0.5.0',
+      io,
+    });
+
+    factory();
+
+    expect(io.stderr.write).toHaveBeenCalledWith(
+      'KTX MCP memory_ingest disabled: missing local memory prerequisites\n',
+    );
+    expect(createDefaultKtxMcpServer).toHaveBeenCalledWith(
+      expect.objectContaining({
+        contextTools: { context_tool: { name: 'context_tool' } },
+      }),
+    );
+  });
+});

packages/cli/src/mcp-server-factory.ts

@@ -41,10 +41,11 @@ export async function createKtxMcpServerFactory(input: {
     cliVersion: input.cliVersion,
     io,
   });
-  const embeddingService =
+  const embeddingProvider =
     resolution.kind === 'configured' || resolution.kind === 'managed-running' || resolution.kind === 'managed-started'
-      ? new KtxIngestEmbeddingPortAdapter(resolution.provider)
+      ? resolution.provider
       : null;
+  const embeddingService = embeddingProvider ? new KtxIngestEmbeddingPortAdapter(embeddingProvider) : null;
   const contextTools = createLocalProjectMcpContextPorts(input.project, {
     semanticLayerCompute,
     queryExecutor,
@@ -57,7 +58,11 @@ export async function createKtxMcpServerFactory(input: {
 
   let memoryIngest: ReturnType<typeof createLocalProjectMemoryIngest> | undefined;
   try {
-    memoryIngest = createLocalProjectMemoryIngest(input.project, { semanticLayerCompute, queryExecutor });
+    memoryIngest = createLocalProjectMemoryIngest(input.project, {
+      semanticLayerCompute,
+      queryExecutor,
+      embeddingProvider,
+    });
   } catch (error) {
     io.stderr.write(`KTX MCP memory_ingest disabled: ${error instanceof Error ? error.message : String(error)}\n`);
   }

packages/context/src/ingest/local-bundle-runtime.test.ts

@@ -111,6 +111,26 @@ describe('createLocalBundleIngestRuntime', () => {
     );
   });
 
+  it('warns when embeddings are configured but no embedding provider is supplied', () => {
+    const logger = { log: vi.fn(), warn: vi.fn(), error: vi.fn() };
+    project.config.ingest.embeddings = {
+      backend: 'openai',
+      model: 'text-embedding-3-small',
+      dimensions: 1536,
+    };
+
+    createLocalBundleIngestRuntime({
+      project,
+      adapters: [new FakeSourceAdapter()],
+      agentRunner: testAgentRunner(),
+      logger: logger as never,
+    });
+
+    expect(logger.warn).toHaveBeenCalledWith(
+      '[local-bundle-runtime] embeddings backend "openai" is configured but no embedding provider was passed; embedding-dependent stages will run against a no-op embedding port.',
+    );
+  });
+
   it('builds runner deps with local SQLite stores and context tools enabled', async () => {
     const agentRunner = testAgentRunner();
 

packages/context/src/ingest/local-bundle-runtime.ts

@@ -671,6 +671,15 @@ export function createLocalBundleIngestRuntime(
   const store = new SqliteBundleIngestStore({ dbPath });
   const contextStore = new SqliteContextEvidenceStore({ dbPath });
   const embeddingProvider = options.embeddingProvider ?? null;
+  if (!embeddingProvider && options.project.config.ingest.embeddings.backend !== 'none') {
+    // Embedding-dependent stages (CandidateDedup clustering, ContextEvidenceIndex
+    // chunk indexing) silently produce zero-vector data with NoopEmbeddingPort.
+    // Surface that fact so the caller knows ingest will not be running its
+    // configured backend.
+    logger.warn(
+      `[local-bundle-runtime] embeddings backend "${options.project.config.ingest.embeddings.backend}" is configured but no embedding provider was passed; embedding-dependent stages will run against a no-op embedding port.`,
+    );
+  }
   const embedding = embeddingProvider ? new KtxIngestEmbeddingPortAdapter(embeddingProvider) : new NoopEmbeddingPort();
   const connections = new LocalConnectionCatalog(options.project, options.queryExecutor);
   const rootFileStore = options.project.fileStore;

packages/context/src/memory/local-memory.test.ts

@@ -88,6 +88,25 @@ describe('createLocalProjectMemoryIngest', () => {
     await rm(tempDir, { recursive: true, force: true });
   });
 
+  it('warns when embeddings are configured but memory ingest is created without an embedding provider', async () => {
+    const project = await initKtxProject({ projectDir: tempDir });
+    project.config.ingest.embeddings = {
+      backend: 'openai',
+      model: 'text-embedding-3-small',
+      dimensions: 1536,
+    };
+    const logger = { log: vi.fn(), warn: vi.fn(), error: vi.fn() };
+
+    createLocalProjectMemoryIngest(project, {
+      agentRunner: { runLoop: vi.fn() } as never,
+      logger: logger as never,
+    });
+
+    expect(logger.warn).toHaveBeenCalledWith(
+      '[memory-ingest] embeddings backend "openai" is configured but no embedding provider was passed; semantic search will fall back to a no-op embedding port.',
+    );
+  });
+
   it('captures a wiki page through the local memory agent and persists pollable status', async () => {
     const project = await initKtxProject({ projectDir: tempDir });
     const agentRunner = {

packages/context/src/memory/local-memory.ts

@@ -5,8 +5,10 @@ import { localConnectionInfoFromConfig } from '../connections/index.js';
 import type { KtxEmbeddingPort, KtxFileStorePort, KtxFileWriteResult } from '../core/index.js';
 import { type KtxLogger, noopLogger, SessionWorktreeService } from '../core/index.js';
 import type { KtxSemanticLayerComputePort } from '../daemon/index.js';
+import type { KtxEmbeddingProvider } from '@ktx/llm';
 import {
   createLocalKtxLlmRuntimeFromConfig,
+  KtxIngestEmbeddingPortAdapter,
   RuntimeAgentRunner,
   type AgentRunnerPort,
   type KtxLlmRuntimePort,
@@ -74,6 +76,7 @@ export interface CreateLocalProjectMemoryIngestOptions {
   queryExecutor?: { execute(input: { connectionId: string; sql: string; maxRows?: number }): Promise<KtxQueryResult> };
   runIdFactory?: () => string;
   logger?: KtxLogger;
+  embeddingProvider?: KtxEmbeddingProvider | null;
 }
 
 export function createLocalProjectMemoryIngest(
@@ -82,7 +85,18 @@ export function createLocalProjectMemoryIngest(
 ): MemoryIngestService {
   const logger = options.logger ?? noopLogger;
   const rootFileStore = new LocalMemoryFileStore(project.fileStore);
-  const embedding = new NoopEmbeddingPort();
+  const embedding = options.embeddingProvider
+    ? new KtxIngestEmbeddingPortAdapter(options.embeddingProvider)
+    : new NoopEmbeddingPort();
+  if (!options.embeddingProvider && project.config.ingest.embeddings.backend !== 'none') {
+    // Memory-agent search (SlSearch, wiki) embeds against this port. With Noop the
+    // configured backend is silently inert — the agent will see empty vectors and
+    // rank results against zeros. Surface that so the caller knows to plumb the
+    // resolved embedding provider through.
+    logger.warn(
+      `[memory-ingest] embeddings backend "${project.config.ingest.embeddings.backend}" is configured but no embedding provider was passed; semantic search will fall back to a no-op embedding port.`,
+    );
+  }
   const knowledgeIndex = new LocalKnowledgeIndex(project);
   const knowledgeEvents = new NoopKnowledgeEventPort();
   const knowledgeSlRefs = new NoopKnowledgeSlRefsPort();

packages/context/src/project/config.test.ts

@@ -176,6 +176,28 @@ llm:
     });
   });
 
+  it('requires a non-empty Vertex location when the Vertex provider block is present', () => {
+    const yaml = `
+llm:
+  provider:
+    backend: vertex
+    vertex:
+      project: local-gcp-project
+`;
+
+    expect(() => parseKtxProjectConfig(yaml)).toThrow(/llm\.provider\.vertex\.location/);
+
+    const validation = validateKtxProjectConfig(yaml);
+    expect(validation.ok).toBe(false);
+    expect(validation.issues).toEqual(
+      expect.arrayContaining([
+        expect.objectContaining({
+          path: 'llm.provider.vertex.location',
+        }),
+      ]),
+    );
+  });
+
   it('parses Claude Code as a first-class LLM backend', () => {
     const config = parseKtxProjectConfig(`
 llm:

packages/context/src/project/config.ts

@@ -30,13 +30,13 @@ const apiCredentialsSchema = z
 const vertexProviderSchema = z
   .strictObject({
     project: z.string().min(1).optional().describe('Google Cloud project ID hosting the Vertex AI endpoint.'),
-    location: z.string().default('').describe('Vertex AI region (e.g. "us-east5"). Empty string falls back to the SDK default.'),
+    location: z.string().min(1).describe('Vertex AI region (e.g. "us-east5"). Required whenever the vertex provider block is present.'),
   })
   .describe('Google Vertex AI provider configuration.');
 
 const sentenceTransformersSchema = z
   .strictObject({
-    base_url: z.string().default('').describe('Base URL of the sentence-transformers HTTP server. Leave empty (or omit) to use the project-managed local daemon.'),
+    base_url: z.string().default('').describe('Base URL of the sentence-transformers HTTP server. Leave empty (or omit) when the `ktx` CLI is expected to start and manage a local daemon for this project; programmatic consumers must populate it explicitly.'),
     pathPrefix: z.string().optional().describe('Optional URL path prefix prepended to embedding requests.'),
   })
   .describe('Sentence-transformers embedding server configuration.');
@@ -83,7 +83,15 @@ const embeddingSchema = z
       .default('none')
       .describe('Embedding backend. "openai" and "sentence-transformers" call out to those providers; "none" disables embeddings.'),
     model: z.string().min(1).optional().describe('Provider-specific embedding model identifier (e.g. "text-embedding-3-small").'),
-    dimensions: z.int().positive().default(8).describe('Embedding vector dimensionality. Must match the chosen model when using a real provider.'),
+    dimensions: z
+      .int()
+      .positive()
+      .default(8)
+      .describe(
+        'Embedding vector dimensionality. The default value 8 is a placeholder that is only valid alongside backend: none; ' +
+          'before switching backend to openai/sentence-transformers, set this explicitly to match the chosen model ' +
+          '(e.g. 384 for all-MiniLM-L6-v2, 1536 for text-embedding-3-small).',
+      ),
     openai: apiCredentialsSchema.optional().describe('OpenAI credentials, used when backend is "openai".'),
     sentenceTransformers: sentenceTransformersSchema.optional().describe('Sentence-transformers server config, used when backend is "sentence-transformers".'),
     batchSize: z.int().positive().optional().describe('Number of texts per embedding API call. Omit to use the backend default.'),

packages/context/src/sl/semantic-layer.service.test.ts

@@ -67,6 +67,23 @@ describe('listConnectionIdsWithNames', () => {
   });
 });
 
+describe('loadSource', () => {
+  it('warns and returns null when an existing source file has invalid YAML', async () => {
+    const logger = { log: vi.fn(), warn: vi.fn(), error: vi.fn() };
+    const configService = {
+      readFile: vi.fn().mockResolvedValue({ content: 'name: [' }),
+    };
+    const service = new SemanticLayerService(configService as never, connectionCatalog(), pythonPort, logger as never);
+
+    await expect(service.loadSource('warehouse', 'orders')).resolves.toBeNull();
+
+    expect(configService.readFile).toHaveBeenCalledWith('semantic-layer/warehouse/orders.yaml');
+    expect(logger.warn).toHaveBeenCalledWith(
+      expect.stringContaining('[loadSource] warehouse/orders.yaml: YAML parse failed:'),
+    );
+  });
+});
+
 describe('composeOverlay', () => {
   it('carries top-level segments from overlay into the composed source', () => {
     const overlay = {
@@ -856,6 +873,22 @@ describe('loadAllSources — standalone enrichment via inherits_columns_from', (
     expect(loadErrors.join('\n')).toContain(overlayPath);
     expect(loadErrors.join('\n')).toContain("move it to 'column_overrides:'");
   });
+
+  it('reports and logs directory listing failures instead of treating them as empty sources', async () => {
+    const logger = { log: vi.fn(), warn: vi.fn(), error: vi.fn() };
+    configService.listFiles.mockRejectedValue(new Error('permission denied'));
+    service = new SemanticLayerService(configService as never, connectionCatalog(), pythonPort, logger as never);
+
+    const { sources, loadErrors } = await service.loadAllSources('conn-1');
+
+    expect(sources).toEqual([]);
+    expect(loadErrors).toEqual([
+      'Failed to list semantic-layer files under semantic-layer/conn-1: permission denied',
+    ]);
+    expect(logger.warn).toHaveBeenCalledWith(
+      'Failed to list semantic-layer files under semantic-layer/conn-1: permission denied',
+    );
+  });
 });
 
 describe('validateWithProposedSource', () => {

packages/context/src/sl/semantic-layer.service.ts

@@ -198,12 +198,25 @@ export class SemanticLayerService {
   }
 
   async loadSource(connectionId: string, sourceName: string): Promise<SemanticLayerSource | null> {
+    let content: string;
     try {
-      const { content } = await this.readSourceFile(connectionId, sourceName);
-      return YAML.parse(content) as SemanticLayerSource;
+      const result = await this.readSourceFile(connectionId, sourceName);
+      content = result.content;
     } catch {
       return null;
     }
+    try {
+      return YAML.parse(content) as SemanticLayerSource;
+    } catch (error) {
+      // Distinguish a YAML parse failure from a missing file. The file exists but
+      // its contents are unparseable — callers that treat null as "does not exist"
+      // could otherwise overwrite the broken file. Surface the parse failure via
+      // the service logger so the broken source is at least visible.
+      this.logger.warn(
+        `[loadSource] ${connectionId}/${sourceName}.yaml: YAML parse failed: ${error instanceof Error ? error.message : String(error)}`,
+      );
+      return null;
+    }
   }
 
   async loadAllSources(connectionId: string): Promise<LoadAllSourcesResult> {
@@ -215,7 +228,10 @@ export class SemanticLayerService {
     try {
       const result = await this.configService.listFiles(dir);
       allFiles = result.files.filter((f) => f.endsWith('.yaml'));
-    } catch {
+    } catch (e) {
+      const message = `Failed to list semantic-layer files under ${dir}: ${e instanceof Error ? e.message : String(e)}`;
+      loadErrors.push(message);
+      this.logger.warn(message);
       return { sources: [], loadErrors };
     }
 

packages/context/src/wiki/knowledge-wiki.service.test.ts

@@ -50,6 +50,27 @@ function makeService() {
 
 const fm: WikiFrontmatter = { summary: 'sum', usage_mode: 'auto' };
 
+describe('KnowledgeWikiService file reads', () => {
+  it('warns and returns null when an existing page cannot be parsed', async () => {
+    const { service, configService, logger } = makeService();
+    configService.readFile.mockResolvedValue({ content: '---\nsummary: [\n---\nBody' });
+
+    await expect(service.readPage('GLOBAL', null, 'revenue')).resolves.toBeNull();
+
+    expect(configService.readFile).toHaveBeenCalledWith('wiki/global/revenue.md');
+    expect(logger.warn).toHaveBeenCalledWith(expect.stringContaining('[readPage] wiki/global/revenue.md: parse failed:'));
+  });
+
+  it('warns and returns an empty page list when directory listing fails', async () => {
+    const { service, configService, logger } = makeService();
+    configService.listFiles.mockRejectedValue(new Error('filesystem unavailable'));
+
+    await expect(service.listPageKeys('GLOBAL', null)).resolves.toEqual([]);
+
+    expect(logger.warn).toHaveBeenCalledWith('[listPageKeys] wiki/global: filesystem unavailable');
+  });
+});
+
 describe('KnowledgeWikiService.syncIndex result stats', () => {
   it('reports scanned, updated, deleted, and embedding counts', async () => {
     const { service, pagesRepository, embeddingService, configService } = makeService();

packages/context/src/wiki/knowledge-wiki.service.ts

@@ -98,13 +98,25 @@ export class KnowledgeWikiService {
 
   async readPage(scope: string, scopeId: string | null | undefined, pageKey: string): Promise<WikiPage | null> {
     const path = this.pagePath(scope, scopeId, pageKey);
+    let raw: string;
     try {
       const result = await this.configService.readFile(path);
-      const { frontmatter, content } = this.parsePage(result.content);
-      return { pageKey, frontmatter, content };
+      raw = result.content;
     } catch {
       return null;
     }
+    try {
+      const { frontmatter, content } = this.parsePage(raw);
+      return { pageKey, frontmatter, content };
+    } catch (error) {
+      // The file exists but parsing failed. Returning null without surfacing the
+      // parse error would let callers (and the memory agent) treat it as "page
+      // doesn't exist" and clobber the broken page on the next write.
+      this.logger.warn(
+        `[readPage] ${path}: parse failed: ${error instanceof Error ? error.message : String(error)}`,
+      );
+      return null;
+    }
   }
 
   async deletePage(
@@ -133,19 +145,23 @@ export class KnowledgeWikiService {
 
   async listPageKeys(scope: string, scopeId?: string | null): Promise<string[]> {
     const dir = this.scopeDir(scope, scopeId);
+    let files: string[];
     try {
       const result = await this.configService.listFiles(dir);
-      return result.files
-        .filter((f) => f.endsWith('.md'))
-        .map((f) => {
-          // Strip the directory prefix and .md extension
-          const name = f.replace(`${dir}/`, '').replace(/\.md$/, '');
-          return name;
-        })
-        .filter(isFlatWikiKey);
-    } catch {
+      files = result.files;
+    } catch (error) {
+      // listFiles returns [] for missing directories; reaching this catch means
+      // an IO-level failure that should at least be surfaced before we report
+      // "no pages" the same as a freshly-initialised store would.
+      this.logger.warn(
+        `[listPageKeys] ${dir}: ${error instanceof Error ? error.message : String(error)}`,
+      );
       return [];
     }
+    return files
+      .filter((f) => f.endsWith('.md'))
+      .map((f) => f.replace(`${dir}/`, '').replace(/\.md$/, ''))
+      .filter(isFlatWikiKey);
   }
 
   async getPageHistory(scope: string, scopeId: string | null | undefined, pageKey: string) {