fix(context): read documented '## P1 — Today' plain tasks in live context (#2186)

resolveTodayTasks only matched a bare '## Today' heading and bold-prefixed
'- [ ] **task**' lines, while the daily-task-manager skill's documented
Output Format writes '## P1 — Today' with plain '- [ ] task' lines — so
documented writes surfaced zero tasks in live context.

Reader now accepts both heading forms and both line forms, two-step: the
legacy bold prefix extracts just the task name (dropping trailing metadata),
falling back to the plain full-line form.

Salvaged from PR #2188 (reader-side half). The skill-doc rewrites in that PR
are dropped: master #2938 kept ops/ synced and made put_page write-through
durable, so the 'gbrain get/put ops/tasks' docs are correct as-is. The PR's
single-regex line matcher is replaced with the two-step match because its
alternation captured '**name** — metadata' verbatim for bold lines.

Takeover of #2188. Fixes #2186.

Co-authored-by: caioribeiroclw-pixel <caioribeiroclw-pixel@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

src/core/context-engine.ts

@@ -453,7 +453,14 @@ function resolveActivity(
  * every `assemble()` call. 1 MB is generous for a human-edited task list. */
 const MAX_TASKS_MD_BYTES = 1_000_000;
 
-/** Extract open tasks from ops/tasks.md "## Today" section. */
+/** Extract open tasks from ops/tasks.md Today section.
+ *
+ * The daily-task-manager skill's documented Output Format uses priority
+ * headings (`## P1 — Today`) with plain `- [ ] task` lines; older fixtures
+ * used a bare `## Today` heading with bold task names. Accept both so the
+ * live-context reader matches the documented writer contract instead of
+ * silently surfacing no tasks (#2186).
+ */
 function resolveTodayTasks(workspaceDir: string): string[] {
   try {
     const path = join(workspaceDir, 'ops', 'tasks.md');
@@ -461,14 +468,18 @@ function resolveTodayTasks(workspaceDir: string): string[] {
     // statSync throws if the file doesn't exist; that lands in the outer catch.
     if (statSync(path).size > MAX_TASKS_MD_BYTES) return [];
     const raw = readFileSync(path, 'utf8');
-    const todayMatch = raw.match(/## Today[\s\S]*?(?=\n## |$)/);
+    const todayMatch = raw.match(/^##\s+(?:P\d\s*[—–-]\s*)?Today\b[\s\S]*?(?=\n##\s|$(?![\s\S]))/m);
     if (!todayMatch) return [];
 
     const lines = todayMatch[0].split('\n');
     const open: string[] = [];
     for (const line of lines) {
-      // Match unchecked task lines: - [ ] **task name** ...
-      const m = line.match(/^\s*-\s*\[ \]\s*\*\*(.+?)\*\*/);
+      // Match unchecked task lines. Legacy bold form first (extracts just
+      // the task name, dropping trailing metadata), then the documented
+      // plain form (whole line body is the task).
+      const m =
+        line.match(/^\s*-\s*\[ \]\s*\*\*(.+?)\*\*/) ??
+        line.match(/^\s*-\s*\[ \]\s*(.+?)\s*$/);
       if (m) open.push(sanitizeForPrompt(m[1].trim()));
     }
     return open.slice(0, 5); // cap at 5 to keep prompt lean

src/core/embedding-dim-check.ts

@@ -14,7 +14,7 @@
  */
 
 import type { BrainEngine } from './engine.ts';
-import { PGVECTOR_HNSW_VECTOR_MAX_DIMS, hnswMaxDimsForType } from './vector-index.ts';
+import { PGVECTOR_HNSW_VECTOR_MAX_DIMS } from './vector-index.ts';
 import { gbrainPath } from './config.ts';
 import { resolveRecipe } from './ai/model-resolver.ts';
 import type { Recipe } from './ai/types.ts';
@@ -609,17 +609,6 @@ export function buildFactsAlterRecipe(
   const opclass = columnType === 'halfvec' ? 'halfvec_cosine_ops' : 'vector_cosine_ops';
   const targetType = columnType === 'halfvec' ? `halfvec(${configuredDims})` : `vector(${configuredDims})`;
   const dimsChanged = columnDims !== configuredDims;
-  const hnswMaxDims = hnswMaxDimsForType(columnType);
-  const indexLines = configuredDims <= hnswMaxDims
-    ? [
-        `CREATE INDEX idx_facts_embedding_hnsw`,
-        `  ON facts USING hnsw (embedding ${opclass})`,
-        `  WHERE embedding IS NOT NULL AND expired_at IS NULL;`,
-      ]
-    : [
-        `-- Skip reindex. ${columnType}(${configuredDims}) exceeds pgvector's HNSW cap of ${hnswMaxDims};`,
-        `-- fact similarity falls back to exact scans.`,
-      ];
   return [
     `-- ALTER ${columnType}(${columnDims}) → ${columnType}(${configuredDims}) on indexed column.`,
     `-- HOLD a maintenance window: this rewrites every row's embedding.`,
@@ -640,7 +629,9 @@ export function buildFactsAlterRecipe(
       : []),
     `ALTER TABLE facts ALTER COLUMN embedding TYPE ${targetType}`,
     `  USING embedding::${targetType};`,
-    ...indexLines,
+    `CREATE INDEX idx_facts_embedding_hnsw`,
+    `  ON facts USING hnsw (embedding ${opclass})`,
+    `  WHERE embedding IS NOT NULL AND expired_at IS NULL;`,
   ].join('\n');
 }
 

src/core/migrate.ts

@@ -1,7 +1,6 @@
 import type { BrainEngine } from './engine.ts';
 import { slugifyPath } from './sync.ts';
 import { getFtsLanguage } from './fts-language.ts';
-import { hnswMaxDimsForType } from './vector-index.ts';
 
 /**
  * Schema migrations — run automatically on initSchema().
@@ -2277,19 +2276,11 @@ export const MIGRATIONS: Migration[] = [
         useHalfvec = true;
       }
 
-      const columnType = useHalfvec ? 'halfvec' : 'vector';
-      const vecType = columnType.toUpperCase();
+      const vecType = useHalfvec ? 'HALFVEC' : 'VECTOR';
       // HNSW operator class must match the column type:
       //   VECTOR(n)  → vector_cosine_ops
       //   HALFVEC(n) → halfvec_cosine_ops
       const opclass = useHalfvec ? 'halfvec_cosine_ops' : 'vector_cosine_ops';
-      const hnswMaxDims = hnswMaxDimsForType(columnType);
-      const factsEmbeddingIndexSql = embeddingDim <= hnswMaxDims
-        ? `CREATE INDEX IF NOT EXISTS idx_facts_embedding_hnsw
-          ON facts USING hnsw (embedding ${opclass})
-          WHERE embedding IS NOT NULL AND expired_at IS NULL;`
-        : `-- idx_facts_embedding_hnsw skipped: pgvector HNSW ${columnType} indexes support
-        -- at most ${hnswMaxDims} dimensions; exact vector scans remain available.`;
       // FK to sources is added in a separate ALTER TABLE rather than inline
       // on the column. Inline `REFERENCES` worked on PGLite but silently
       // got dropped by postgres.js's `unsafe()` multi-statement path on
@@ -2363,7 +2354,9 @@ export const MIGRATIONS: Migration[] = [
           ON facts(source_id, entity_slug)
           WHERE consolidated_at IS NULL AND expired_at IS NULL;
 
-        ${factsEmbeddingIndexSql}
+        CREATE INDEX IF NOT EXISTS idx_facts_embedding_hnsw
+          ON facts USING hnsw (embedding ${opclass})
+          WHERE embedding IS NOT NULL AND expired_at IS NULL;
       `;
 
       await engine.runMigration(40, factsDDL);
@@ -2877,16 +2870,8 @@ export const MIGRATIONS: Migration[] = [
         useHalfvec = true;
       }
 
-      const columnType = useHalfvec ? 'halfvec' : 'vector';
-      const vecType = columnType.toUpperCase();
+      const vecType = useHalfvec ? 'HALFVEC' : 'VECTOR';
       const opclass = useHalfvec ? 'halfvec_cosine_ops' : 'vector_cosine_ops';
-      const hnswMaxDims = hnswMaxDimsForType(columnType);
-      const queryCacheEmbeddingIndexSql = embeddingDim <= hnswMaxDims
-        ? `CREATE INDEX IF NOT EXISTS idx_query_cache_embedding_hnsw
-          ON query_cache USING hnsw (embedding ${opclass})
-          WHERE embedding IS NOT NULL;`
-        : `-- idx_query_cache_embedding_hnsw skipped: pgvector HNSW ${columnType} indexes support
-        -- at most ${hnswMaxDims} dimensions; exact vector scans remain available.`;
 
       const ddl = `
         CREATE TABLE IF NOT EXISTS query_cache (
@@ -2905,7 +2890,9 @@ export const MIGRATIONS: Migration[] = [
         CREATE INDEX IF NOT EXISTS idx_query_cache_source_created
           ON query_cache(source_id, created_at DESC);
 
-        ${queryCacheEmbeddingIndexSql}
+        CREATE INDEX IF NOT EXISTS idx_query_cache_embedding_hnsw
+          ON query_cache USING hnsw (embedding ${opclass})
+          WHERE embedding IS NOT NULL;
       `;
 
       await engine.runMigration(55, ddl);

src/core/vector-index.ts

@@ -17,7 +17,6 @@
 import type { BrainEngine } from './engine.ts';
 
 export const PGVECTOR_HNSW_VECTOR_MAX_DIMS = 2000;
-export const PGVECTOR_HNSW_HALFVEC_MAX_DIMS = 4000;
 
 const CHUNK_EMBEDDING_HNSW_INDEX =
   'CREATE INDEX IF NOT EXISTS idx_chunks_embedding ON content_chunks USING hnsw (embedding vector_cosine_ops);';
@@ -30,10 +29,6 @@ export function chunkEmbeddingIndexSql(dims: number): string {
   ].join('\n');
 }
 
-export function hnswMaxDimsForType(columnType: 'vector' | 'halfvec'): number {
-  return columnType === 'halfvec' ? PGVECTOR_HNSW_HALFVEC_MAX_DIMS : PGVECTOR_HNSW_VECTOR_MAX_DIMS;
-}
-
 export function applyChunkEmbeddingIndexPolicy(sql: string, dims: number): string {
   return sql.replaceAll(CHUNK_EMBEDDING_HNSW_INDEX, chunkEmbeddingIndexSql(dims));
 }

test/context-engine.test.ts

@@ -322,6 +322,28 @@ describe('gbrain-context engine', () => {
     expect(result.systemPromptAddition).not.toContain('Something later');
   });
 
+  it('injects documented "## P1 — Today" plain tasks from ops/tasks.md (#2186)', async () => {
+    tmpDir = makeWorkspace({
+      heartbeat: { garryAwake: true },
+      tasks: `# Tasks\n\n## P0 — Urgent\n- [ ] **Escalate outage**\n\n## P1 — Today\n- [ ] Call Alice about launch plan\n- [ ] **Review Bob contract** — due Friday\n- [x] Completed item\n\n## P2 — This Week\n- [ ] Should not surface`,
+    });
+    const engine = createGBrainContextEngine({ workspaceDir: tmpDir });
+
+    const result = await engine.assemble({
+      sessionId: 'test-session',
+      messages: [],
+    });
+
+    expect(result.systemPromptAddition).toContain('Open tasks');
+    expect(result.systemPromptAddition).toContain('Call Alice about launch plan');
+    // Bold form still extracts just the task name, not trailing metadata.
+    expect(result.systemPromptAddition).toContain('Review Bob contract');
+    expect(result.systemPromptAddition).not.toContain('due Friday');
+    expect(result.systemPromptAddition).not.toContain('Escalate outage');
+    expect(result.systemPromptAddition).not.toContain('Completed item');
+    expect(result.systemPromptAddition).not.toContain('Should not surface');
+  });
+
   it('no activity section when calendar is empty and no tasks', async () => {
     tmpDir = makeWorkspace({
       heartbeat: { garryAwake: true },

test/embedding-dim-check-facts.test.ts

@@ -122,9 +122,9 @@ describe('buildFactsAlterRecipe', () => {
   });
 
   test('vector recipe uses vector_cosine_ops + vector(N) USING cast', () => {
-    const recipe = buildFactsAlterRecipe(1024, 1536, 'vector');
-    expect(recipe).toContain('vector(1536)');
-    expect(recipe).toContain('USING embedding::vector(1536)');
+    const recipe = buildFactsAlterRecipe(1024, 2048, 'vector');
+    expect(recipe).toContain('vector(2048)');
+    expect(recipe).toContain('USING embedding::vector(2048)');
     expect(recipe).toContain('vector_cosine_ops');
     expect(recipe).not.toContain('halfvec_cosine_ops');
   });
@@ -163,14 +163,6 @@ describe('buildFactsAlterRecipe', () => {
     expect(recipe).not.toContain('UPDATE facts SET embedding = NULL');
     expect(recipe).toContain('USING embedding::vector(1536)');
   });
-
-  test('halfvec recipe skips HNSW rebuild above pgvector cap', () => {
-    const recipe = buildFactsAlterRecipe(1536, 4096, 'halfvec');
-    expect(recipe).toContain('halfvec(4096)');
-    expect(recipe).toContain('Skip reindex');
-    expect(recipe).toContain("exceeds pgvector's HNSW cap of 4000");
-    expect(recipe).not.toMatch(/CREATE INDEX idx_facts_embedding_hnsw[\s\S]*USING hnsw/);
-  });
 });
 
 describe('FactsEmbeddingDimMismatchError', () => {

test/facts-migration-dim.test.ts

@@ -11,7 +11,6 @@
 
 import { describe, test, expect, beforeAll, afterAll } from 'bun:test';
 import { PGLiteEngine } from '../src/core/pglite-engine.ts';
-import { configureGateway, resetGateway } from '../src/core/ai/gateway.ts';
 
 let engine: PGLiteEngine;
 
@@ -94,60 +93,4 @@ describe('migration v45 facts column shape', () => {
     );
     expect(after[0].udt_name).toBe(before[0].udt_name);
   });
-
-});
-
-describe('migration v45/v55 large-dim HNSW policy', () => {
-  let largeDimEngine: PGLiteEngine;
-
-  beforeAll(async () => {
-    configureGateway({
-      embedding_model: 'litellm:custom-4096d',
-      embedding_dimensions: 4096,
-      env: { ...process.env },
-    });
-
-    largeDimEngine = new PGLiteEngine();
-    await largeDimEngine.connect({});
-    await largeDimEngine.initSchema();
-  });
-
-  afterAll(async () => {
-    await largeDimEngine.disconnect();
-    resetGateway();
-  });
-
-  test('4096d init skips unsupported HNSW indexes but keeps vector columns', async () => {
-    const formatRows = await largeDimEngine.executeRaw<{ format_type: string }>(
-      `SELECT format_type(atttypid, atttypmod) AS format_type
-       FROM pg_attribute
-       WHERE attrelid = 'facts'::regclass AND attname = 'embedding'`,
-    );
-    expect(formatRows[0]?.format_type).toMatch(/(halfvec|vector)\(4096\)/);
-
-    const indexRows = await largeDimEngine.executeRaw<{ exists: boolean }>(
-      `SELECT EXISTS (
-         SELECT 1 FROM pg_indexes
-         WHERE tablename = 'facts'
-           AND indexname = 'idx_facts_embedding_hnsw'
-       ) AS exists`,
-    );
-    expect(indexRows[0]?.exists).toBe(false);
-
-    const queryCacheFormatRows = await largeDimEngine.executeRaw<{ format_type: string }>(
-      `SELECT format_type(atttypid, atttypmod) AS format_type
-       FROM pg_attribute
-       WHERE attrelid = 'query_cache'::regclass AND attname = 'embedding'`,
-    );
-    expect(queryCacheFormatRows[0]?.format_type).toMatch(/(halfvec|vector)\(4096\)/);
-
-    const queryCacheIndexRows = await largeDimEngine.executeRaw<{ exists: boolean }>(
-      `SELECT EXISTS (
-         SELECT 1 FROM pg_indexes
-         WHERE tablename = 'query_cache'
-           AND indexname = 'idx_query_cache_embedding_hnsw'
-       ) AS exists`,
-    );
-    expect(queryCacheIndexRows[0]?.exists).toBe(false);
-  }, 60000);
 });