docs(tutorial): drop dead --remote flag from company-brain search examples

With unknown op flags now a hard error (this PR), the tutorial's
`gbrain search ... --remote` invocations would fail: no code path ever
read a --remote flag — thin-client installs route shared ops through the
remote MCP server automatically. Update the three examples to the
flagless form and explain the automatic routing.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

docs/tutorials/company-brain.md

@@ -223,14 +223,16 @@ export GBRAIN_REMOTE_CLIENT_ID=<Alice's client_id>
 export GBRAIN_REMOTE_CLIENT_SECRET=<Alice's client_secret>
 export GBRAIN_REMOTE_MCP_URL=https://brain.acme-co.com/mcp
 
-gbrain search "performance review" --remote
+gbrain search "performance review"
 ```
 
+(On a thin-client install every shared op routes through the remote MCP server automatically — no flag needed. The env vars select whose credentials the call uses.)
+
 Alice should see results only from `customers` and `shared`. The performance-review notes live in `internal`, which she's not scoped to read. She shouldn't see them.
 
 ```bash
 # Terminal 2, as Bob (export his credentials similarly)
-gbrain search "performance review" --remote
+gbrain search "performance review"
 ```
 
 Bob should see the performance-review notes from `internal`, plus anything related from `shared`. He shouldn't see anything that lives only in `customers`.
@@ -514,7 +516,7 @@ The first sync embeds every page, which takes time. Check `gbrain sources status
 
 ### "I see a page I shouldn't see"
 
-This shouldn't happen, but if you suspect it, run `gbrain search <query> --remote --json` as the constrained client and inspect the `source_id` field on every returned result. Every row should be in the client's `--federated-read` set. If one isn't, file an issue with the exact slug and source IDs.
+This shouldn't happen, but if you suspect it, run `gbrain search <query> --json` as the constrained client (thin-client install, with the client's `GBRAIN_REMOTE_*` env exported) and inspect the `source_id` field on every returned result. Every row should be in the client's `--federated-read` set. If one isn't, file an issue with the exact slug and source IDs.
 
 ### "The synthesized answer is wrong"
 

src/cli.ts

@@ -464,7 +464,11 @@ async function main() {
     // routed path. Date → ISO string; bigint → string (postgres.js shape);
     // Buffer → object. Microsecond-cost; eliminates a whole drift bug class.
     const result = JSON.parse(JSON.stringify(rawResult, bigintToStringReplacer));
-    const output = formatResult(op.name, result);
+    // #380 pass-through: `--json` (undeclared on most ops, promised by docs)
+    // emits the raw op result instead of the human formatter.
+    const output = params.json === true
+      ? JSON.stringify(result, null, 2) + '\n'
+      : formatResult(op.name, result);
     if (output) process.stdout.write(output);
   } catch (e: unknown) {
     // v0.42.20.0 (codex D4): on error, set exitCode + return so the `finally`
@@ -547,7 +551,10 @@ async function runThinClientRouted(
       signal: sigintController.signal,
     });
     const result = unpackToolResult(raw);
-    const output = formatResult(op.name, result);
+    // #380: same --json seam as the local-engine path (renderer parity).
+    const output = params.json === true
+      ? JSON.stringify(result, null, 2) + '\n'
+      : formatResult(op.name, result);
     if (output) process.stdout.write(output);
   } catch (e: unknown) {
     if (e instanceof RemoteMcpError) {
@@ -757,10 +764,28 @@ export function resolveQueryImage(
   return { path: imagePath, base64, mime };
 }
 
+/**
+ * #380: undeclared flags that are honored DOWNSTREAM of parseOpArgs and must
+ * keep passing through when unknown flags become hard errors:
+ *   - source     → makeContext's resolveSourceId (the --source axis)
+ *   - brain      → the mount/brain routing axis (docs promise the flag)
+ *   - dry_run    → makeContext's ctx.dryRun (ops without a declared dry_run)
+ *   - json       → raw-JSON output seam (local + thin-client paths)
+ */
+const PASSTHROUGH_VALUE_FLAGS = new Set(['source', 'brain']);
+const PASSTHROUGH_BOOL_FLAGS = new Set(['dry_run', 'json']);
+
 export function parseOpArgs(op: Operation, args: string[]): Record<string, unknown> {
   const params: Record<string, unknown> = {};
   const positional = op.cliHints?.positional || [];
   let posIdx = 0;
+  const cliName = op.cliHints?.name || op.name;
+  const MAX_STDIN = 5_000_000; // 5MB cap, shared by stdin and --file
+  // #380: `--file <path>` fills the op's declared stdin param (put's `content`)
+  // from a file. Driven by cliHints.stdin — no per-op hard-coding — and
+  // disabled when the op declares a real `file` param of its own.
+  const fileParam = op.cliHints?.stdin && !op.params.file ? op.cliHints.stdin : undefined;
+  let filePath: string | undefined;
 
   for (let i = 0; i < args.length; i++) {
     const arg = args[i];
@@ -774,12 +799,42 @@ export function parseOpArgs(op: Operation, args: string[]): Record<string, unkno
         }
       }
       const key = arg.slice(2).replace(/-/g, '_');
+      if (fileParam && key === 'file') {
+        if (i + 1 >= args.length) {
+          console.error(`Error: ${arg} requires a value.`);
+          process.exit(1);
+        }
+        filePath = args[++i];
+        continue;
+      }
       const paramDef = op.params[key];
-      if (paramDef?.type === 'boolean') {
+      if (!paramDef) {
+        if (PASSTHROUGH_BOOL_FLAGS.has(key)) {
+          params[key] = true;
+          continue;
+        }
+        if (PASSTHROUGH_VALUE_FLAGS.has(key)) {
+          if (i + 1 >= args.length) {
+            console.error(`Error: ${arg} requires a value.`);
+            process.exit(1);
+          }
+          params[key] = args[++i];
+          continue;
+        }
+        // #380: unknown flags were silently swallowed into params, so typos
+        // like `put --file` created empty pages instead of erroring.
+        console.error(`Unknown option for gbrain ${cliName}: ${arg}`);
+        console.error(`Run 'gbrain ${cliName} --help' for valid flags.`);
+        process.exit(1);
+      }
+      if (paramDef.type === 'boolean') {
         params[key] = true;
       } else if (i + 1 < args.length) {
         params[key] = args[++i];
-        if (paramDef?.type === 'number') params[key] = Number(params[key]);
+        if (paramDef.type === 'number') params[key] = Number(params[key]);
+      } else {
+        console.error(`Error: ${arg} requires a value.`);
+        process.exit(1);
       }
     } else if (posIdx < positional.length) {
       const key = positional[posIdx++];
@@ -788,10 +843,30 @@ export function parseOpArgs(op: Operation, args: string[]): Record<string, unkno
     }
   }
 
+  // #380: resolve --file AFTER the loop so --file/--content conflicts are
+  // caught in either order.
+  if (filePath !== undefined && fileParam) {
+    if (params[fileParam] !== undefined) {
+      console.error(`Error: use only one of --file, --${fileParam}, or stdin for gbrain ${cliName}.`);
+      process.exit(1);
+    }
+    let fileContent: string;
+    try {
+      fileContent = readFileSync(filePath, 'utf-8');
+    } catch (e) {
+      console.error(`Error: cannot read --file ${filePath}: ${e instanceof Error ? e.message : String(e)}`);
+      process.exit(1);
+    }
+    if (Buffer.byteLength(fileContent, 'utf-8') > MAX_STDIN) {
+      console.error(`Error: file content exceeds ${MAX_STDIN} bytes. Split into smaller inputs.`);
+      process.exit(1);
+    }
+    params[fileParam] = fileContent;
+  }
+
   // Read stdin for content params
   if (op.cliHints?.stdin && !params[op.cliHints.stdin] && !process.stdin.isTTY) {
     const stdinContent = readFileSync(0, 'utf-8');
-    const MAX_STDIN = 5_000_000; // 5MB
     if (Buffer.byteLength(stdinContent, 'utf-8') > MAX_STDIN) {
       console.error(`Error: stdin content exceeds ${MAX_STDIN} bytes. Split into smaller inputs.`);
       process.exit(1);
@@ -2253,6 +2328,10 @@ export function printOpHelp(op: Operation, invokedName?: string) {
       const prefix = isPos ? `  <${key}>` : `  --${key.replace(/_/g, '-')}`;
       console.log(`${prefix.padEnd(28)} ${def.description || ''}${req}`);
     }
+    // #380: ops that read stdin also accept --file <path> (parseOpArgs).
+    if (op.cliHints?.stdin && !op.params.file) {
+      console.log(`${'  --file <path>'.padEnd(28)} Read ${op.cliHints.stdin} from a file (alternative to --${op.cliHints.stdin} or stdin)`);
+    }
   }
 }
 

src/commands/embed.ts

@@ -1,5 +1,5 @@
 import type { BrainEngine } from '../core/engine.ts';
-import { embedBatch, currentEmbeddingSignature, resolveEmbeddingModelLabel } from '../core/embedding.ts';
+import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
 import type { ChunkInput } from '../core/types.ts';
 import { chunkText } from '../core/chunkers/recursive.ts';
 import { createProgress, type ProgressReporter } from '../core/progress.ts';
@@ -581,16 +581,11 @@ async function embedPage(
   for (let j = 0; j < toEmbed.length; j++) {
     embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
   }
-  // #1717: label each (re)embedded chunk with the model that actually
-  // produced its vector. Preserved chunks (not re-embedded this pass) keep
-  // their existing model so a mixed-model page isn't relabeled wholesale.
-  const embedModelLabel = resolveEmbeddingModelLabel();
   const updated: ChunkInput[] = chunks.map(c => ({
     chunk_index: c.chunk_index,
     chunk_text: c.chunk_text,
     chunk_source: c.chunk_source,
     embedding: embeddingMap.get(c.chunk_index),
-    model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
     token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
   }));
 
@@ -722,16 +717,12 @@ async function embedAll(
       for (let j = 0; j < toEmbed.length; j++) {
         embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
       }
-      // #1717: stamp the resolved embedding model on (re)embedded chunks;
-      // preserve the existing model on chunks left untouched.
-      const embedModelLabel = resolveEmbeddingModelLabel();
       // Preserve ALL chunks, only update embeddings for stale ones
       const updated: ChunkInput[] = chunks.map(c => ({
         chunk_index: c.chunk_index,
         chunk_text: c.chunk_text,
         chunk_source: c.chunk_source,
         embedding: embeddingMap.get(c.chunk_index) ?? undefined,
-        model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
         token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
       }));
       await observed(pacer, () => engine.upsertChunks(page.slug, updated, pageOpts));
@@ -1021,15 +1012,11 @@ async function embedAllStale(
           for (let j = 0; j < stale.length; j++) {
             staleIdxToEmbedding.set(stale[j].chunk_index, embeddings[j]);
           }
-          // #1717: label the re-embedded (stale) chunks with the resolved
-          // model; preserve the existing model on the non-stale chunks.
-          const embedModelLabel = resolveEmbeddingModelLabel();
           const merged: ChunkInput[] = existing.map(c => ({
             chunk_index: c.chunk_index,
             chunk_text: c.chunk_text,
             chunk_source: c.chunk_source,
             embedding: staleIdxToEmbedding.get(c.chunk_index) ?? undefined,
-            model: staleIdxToEmbedding.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
             token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
           }));
           await observed(pacer, () => engine.upsertChunks(slug, merged, { sourceId: keySourceId }));

src/core/embed-stale.ts

@@ -20,7 +20,6 @@
 import type { BrainEngine } from './engine.ts';
 import type { ChunkInput } from './types.ts';
 import { embedBatchWithBackoff } from '../commands/embed.ts';
-import { resolveEmbeddingModelLabel } from './embedding.ts';
 import { type DbPacer, createNoopPacer, observed } from './db-pacer.ts';
 import { AbortError } from './abort-check.ts';
 
@@ -201,17 +200,11 @@ export async function embedStaleForSource(
         for (let j = 0; j < stale.length; j++) {
           staleIdxToEmbedding.set(stale[j].chunk_index, embeddings[j]);
         }
-        // #1717: label re-embedded chunks with the model that produced the
-        // vector; preserved chunks keep their existing model. Without this,
-        // upsertChunks falls back to DEFAULT_EMBEDDING_MODEL for every chunk
-        // (the same mislabel the embed.ts paths fixed).
-        const embedModelLabel = resolveEmbeddingModelLabel();
         const merged: ChunkInput[] = existing.map((c) => ({
           chunk_index: c.chunk_index,
           chunk_text: c.chunk_text,
           chunk_source: c.chunk_source,
           embedding: staleIdxToEmbedding.get(c.chunk_index) ?? undefined,
-          model: staleIdxToEmbedding.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
           token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
           // Carry through per-chunk metadata. upsertChunks writes these as
           // EXCLUDED.<col> (not COALESCE), so omitting them here resets image

src/core/embedding.ts

@@ -113,21 +113,6 @@ export async function embedBatch(
   return results;
 }
 
-/**
- * Resolve the embedding model label (`provider:model`) to stamp onto
- * `content_chunks.model`, so each chunk records the model that actually
- * produced its vector instead of the engine's hardcoded default (#1717).
- * Returns undefined if the gateway is unconfigured; callers then fall back
- * to the chunk's existing model rather than mislabeling it.
- */
-export function resolveEmbeddingModelLabel(): string | undefined {
-  try {
-    return gatewayGetModel();
-  } catch {
-    return undefined;
-  }
-}
-
 /** Currently-configured embedding model (short form without provider prefix). */
 export function getEmbeddingModelName(): string {
   return gatewayGetModel().split(':').slice(1).join(':') || 'text-embedding-3-large';

src/core/import-file.ts

@@ -8,7 +8,7 @@ import { chunkText } from './chunkers/recursive.ts';
 import { chunkCodeText, chunkCodeTextFull, detectCodeLanguage, CHUNKER_VERSION } from './chunkers/code.ts';
 import { findChunkForOffset } from './chunkers/edge-extractor.ts';
 import { extractCodeRefs, imageOfCandidates } from './link-extraction.ts';
-import { embedBatch, embedMultimodal, currentEmbeddingSignature, resolveEmbeddingModelLabel } from './embedding.ts';
+import { embedBatch, embedMultimodal, currentEmbeddingSignature } from './embedding.ts';
 import { slugifyPath, slugifyCodePath, isCodeFilePath } from './sync.ts';
 import type { ChunkInput, PageInput, PageType } from './types.ts';
 import { computeEffectiveDate } from './effective-date.ts';
@@ -716,12 +716,8 @@ export async function importFromContent(
       ? chunks.map((c) => wrapChunkForEmbedding(c.chunk_text, prefix, c.chunk_source))
       : chunks.map((c) => c.chunk_text);
     const embeddings = await embedBatch(wrappedTexts);
-    // #1717: label each chunk with the model that actually produced its
-    // vector, not the engine's hardcoded default.
-    const embedModelLabel = resolveEmbeddingModelLabel();
     for (let i = 0; i < chunks.length; i++) {
       chunks[i].embedding = embeddings[i];
-      if (embedModelLabel) chunks[i].model = embedModelLabel;
       // token_count tracks the wrapped string length so cost reporting
       // reflects what we actually sent to the embedder.
       chunks[i].token_count = Math.ceil(wrappedTexts[i].length / 4);
@@ -1145,10 +1141,7 @@ export async function importCodeFile(
     const matched = existingByKey.get(key);
     if (matched && matched.embedding) {
       // Reuse the existing embedding verbatim. No API call, no cost.
-      // #1717: carry the existing model label along with the reused vector
-      // so the upsert doesn't relabel it with the engine default.
       chunks[i]!.embedding = matched.embedding as Float32Array;
-      chunks[i]!.model = matched.model ?? undefined;
       chunks[i]!.token_count = matched.token_count ?? undefined;
     } else {
       needsEmbedIndexes.push(i);
@@ -1160,12 +1153,9 @@ export async function importCodeFile(
     try {
       const textsToEmbed = needsEmbedIndexes.map((i) => chunks[i]!.chunk_text);
       const embeddings = await embedBatch(textsToEmbed);
-      // #1717: stamp the model that produced these vectors.
-      const embedModelLabel = resolveEmbeddingModelLabel();
       for (let j = 0; j < needsEmbedIndexes.length; j++) {
         const i = needsEmbedIndexes[j]!;
         chunks[i]!.embedding = embeddings[j]!;
-        if (embedModelLabel) chunks[i]!.model = embedModelLabel;
         chunks[i]!.token_count = Math.ceil(chunks[i]!.chunk_text.length / 4);
       }
     } catch (e: unknown) {

src/core/operations.ts

@@ -769,7 +769,7 @@ const get_page: Operation = {
 
 const put_page: Operation = {
   name: 'put_page',
-  description: 'Write/update a page (markdown with frontmatter). Chunks, embeds, reconciles tags, and (when auto_link/auto_timeline are enabled) extracts + reconciles graph links and timeline entries. For large content on Windows (pipe-buffer limit ~45KB) or any file-as-input workflow, use `gbrain capture --file PATH --slug SLUG` — capture reads the file as a Buffer with a binary-NUL guard and adds provenance write-through (v0.39.3.0).',
+  description: 'Write/update a page (markdown with frontmatter). Chunks, embeds, reconciles tags, and (when auto_link/auto_timeline are enabled) extracts + reconciles graph links and timeline entries. On the CLI, `gbrain put SLUG --file PATH` reads content from a file (also `--content` or stdin). For provenance write-through and a binary-NUL guard, prefer `gbrain capture --file PATH --slug SLUG` (v0.39.3.0).',
   params: {
     slug: { type: 'string', required: true, description: 'Page slug' },
     content: { type: 'string', required: true, description: 'Full markdown content with YAML frontmatter' },
@@ -1384,7 +1384,10 @@ const list_pages: Operation = {
   params: {
     type: { type: 'string', description: 'Filter by page type' },
     tag: { type: 'string', description: 'Filter by tag' },
-    limit: { type: 'number', description: 'Max results (default 50)' },
+    limit: { type: 'number', description: 'Max results (default 50, capped at 100 — use offset to paginate beyond)' },
+    // #2876: the 100-row cap was silent and there was no way past it even
+    // though both engines already support OFFSET on listPages.
+    offset: { type: 'number', description: 'Skip first N results (pagination; pair with limit)' },
     // v0.29 — surface filter that already exists on PageFilters.
     updated_after: {
       type: 'string',
@@ -1415,6 +1418,10 @@ const list_pages: Operation = {
       type: p.type as any,
       tag: p.tag as string,
       limit: clampSearchLimit(p.limit as number | undefined, 50, 100),
+      // #2876: thread pagination through (engines already honor offset).
+      offset: Number.isFinite(p.offset as number) && (p.offset as number) > 0
+        ? Math.floor(p.offset as number)
+        : undefined,
       includeDeleted: (p.include_deleted as boolean) === true,
       updated_after: typeof p.updated_after === 'string' ? p.updated_after : undefined,
       sort,

test/cli-args.test.ts

@@ -1,8 +1,41 @@
 import { describe, expect, test } from 'bun:test';
+import { mkdtempSync, rmSync, writeFileSync } from 'fs';
+import { tmpdir } from 'os';
+import { join } from 'path';
 import { parseOpArgs } from '../src/cli.ts';
 import { operationsByName } from '../src/core/operations.ts';
 
 describe('parseOpArgs', () => {
+  // #380: `gbrain put SLUG --file PATH` reads content from the file instead
+  // of silently swallowing the flag and creating an empty page.
+  test('put --file reads the stdin param (content) from a file', () => {
+    const dir = mkdtempSync(join(tmpdir(), 'gbrain-put-file-'));
+    try {
+      const pagePath = join(dir, 'page.md');
+      writeFileSync(pagePath, '# From file\n\nBody loaded from --file.\n');
+      const params = parseOpArgs(operationsByName.put_page, ['concepts/from-file', '--file', pagePath]);
+      expect(params.slug).toBe('concepts/from-file');
+      expect(params.content).toBe('# From file\n\nBody loaded from --file.\n');
+    } finally {
+      rmSync(dir, { recursive: true, force: true });
+    }
+  });
+
+  // #380 regression guard: undeclared-but-honored flags must keep passing
+  // through when unknown flags become hard errors (--source is read by
+  // makeContext; --json by the output seam; --dry-run by ctx.dryRun).
+  test('pass-through allowlist flags survive on ops that do not declare them', () => {
+    const params = parseOpArgs(operationsByName.get_page, [
+      'people/alice-example', '--source', 'wiki', '--json', '--dry-run',
+    ]);
+    expect(params).toEqual({
+      slug: 'people/alice-example',
+      source: 'wiki',
+      json: true,
+      dry_run: true,
+    });
+  });
+
   test('--no-<boolean> maps to false without consuming the next flag', () => {
     const params = parseOpArgs(operationsByName.query, [
       'freshEmbedSourceScope code source',

test/cli.test.ts

@@ -1,5 +1,5 @@
 import { describe, test, expect } from 'bun:test';
-import { existsSync, mkdtempSync, readFileSync, rmSync } from 'fs';
+import { existsSync, mkdtempSync, readFileSync, rmSync, writeFileSync } from 'fs';
 import { tmpdir } from 'os';
 import { join } from 'path';
 
@@ -120,6 +120,76 @@ describe('CLI dispatch integration', () => {
     expect(exitCode).toBe(0);
   });
 
+  // #380 / PR #856: put --help documents the --file input path.
+  test('put --help documents --file input', async () => {
+    const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'put', '--help'], {
+      cwd: repoRoot,
+      stdout: 'pipe',
+      stderr: 'pipe',
+    });
+    const stdout = await new Response(proc.stdout).text();
+    const exitCode = await proc.exited;
+    expect(stdout).toContain('Usage: gbrain put');
+    expect(stdout).toContain('--file <path>');
+    expect(exitCode).toBe(0);
+  });
+
+  // #380: unknown flags on shared ops are a hard error (previously silently
+  // swallowed into params — `put --file` created empty pages). parseOpArgs
+  // runs BEFORE engine connect, so the error must fire without a brain.
+  test('unknown shared-op flags fail before DB connection', async () => {
+    const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-unknown-flag-'));
+    try {
+      const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'get', 'people/alice', '--bogus'], {
+        cwd: repoRoot,
+        stdout: 'pipe',
+        stderr: 'pipe',
+        env: isolatedEnv(home),
+      });
+      const stderr = await new Response(proc.stderr).text();
+      const exitCode = await proc.exited;
+      expect(stderr).toContain('Unknown option for gbrain get: --bogus');
+      expect(stderr).not.toContain('No brain configured');
+      expect(exitCode).toBe(1);
+    } finally {
+      rmSync(home, { recursive: true, force: true });
+    }
+  });
+
+  test('put rejects combining --file and --content', async () => {
+    const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-put-conflict-'));
+    try {
+      const pagePath = join(home, 'page.md');
+      writeFileSync(pagePath, 'file body\n');
+      const proc = Bun.spawn(
+        ['bun', 'run', 'src/cli.ts', 'put', 'a/b', '--content', 'inline', '--file', pagePath],
+        { cwd: repoRoot, stdout: 'pipe', stderr: 'pipe', env: isolatedEnv(home) },
+      );
+      const stderr = await new Response(proc.stderr).text();
+      const exitCode = await proc.exited;
+      expect(stderr).toContain('use only one of --file, --content, or stdin');
+      expect(exitCode).toBe(1);
+    } finally {
+      rmSync(home, { recursive: true, force: true });
+    }
+  });
+
+  test('put --file with a missing path errors instead of writing an empty page', async () => {
+    const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-put-missing-file-'));
+    try {
+      const proc = Bun.spawn(
+        ['bun', 'run', 'src/cli.ts', 'put', 'a/b', '--file', join(home, 'nope.md')],
+        { cwd: repoRoot, stdout: 'pipe', stderr: 'pipe', env: isolatedEnv(home) },
+      );
+      const stderr = await new Response(proc.stderr).text();
+      const exitCode = await proc.exited;
+      expect(stderr).toContain('cannot read --file');
+      expect(exitCode).toBe(1);
+    } finally {
+      rmSync(home, { recursive: true, force: true });
+    }
+  });
+
   test('upgrade --help prints usage without running upgrade', async () => {
     const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'upgrade', '--help'], {
       cwd: repoRoot,

test/embed-stale.serial.test.ts

@@ -15,7 +15,6 @@ import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:tes
 import { PGLiteEngine } from '../src/core/pglite-engine.ts';
 import { resetPgliteState } from './helpers/reset-pglite.ts';
 import { embedStaleForSource } from '../src/core/embed-stale.ts';
-import { configureGateway, resetGateway } from '../src/core/ai/gateway.ts';
 import type { ChunkInput } from '../src/core/types.ts';
 
 let engine: PGLiteEngine;
@@ -277,49 +276,4 @@ describe('embedStaleForSource', () => {
     // The stale text row actually got its embedding.
     expect(txtRow.embedded_at).not.toBeNull();
   });
-
-  // #1717: the backfill path must label re-embedded chunks with the model
-  // that produced the vector, and preserve the existing label on chunks it
-  // did not touch (before the fix, both were reset to the engine default).
-  test('labels re-embedded chunks with the gateway model, preserves untouched labels (#1717)', async () => {
-    configureGateway({
-      embedding_model: 'openai:text-embedding-3-large',
-      env: { OPENAI_API_KEY: 'sk-test-embed-stale-1717' },
-    });
-    try {
-      await engine.putPage('notes/model-label', {
-        type: 'note',
-        title: 'model-label',
-        compiled_truth: '# model-label\n\nseeded',
-      });
-      await engine.upsertChunks('notes/model-label', [
-        {
-          chunk_index: 0,
-          chunk_text: 'already embedded elsewhere',
-          chunk_source: 'compiled_truth',
-          embedding: new Float32Array(1536).fill(0.01),
-          model: 'voyage:voyage-3',
-          token_count: 4,
-        },
-        {
-          chunk_index: 1,
-          chunk_text: 'stale chunk needing embed',
-          chunk_source: 'compiled_truth',
-          token_count: 5,
-          embedding: undefined, // stale
-        },
-      ]);
-
-      const result = await embedStaleForSource(engine, 'default', { embedFn: fakeEmbedFn });
-      expect(result.embedded).toBe(1);
-
-      const after = await engine.getChunks('notes/model-label');
-      const preserved = after.find((c) => c.chunk_index === 0)!;
-      const reembedded = after.find((c) => c.chunk_index === 1)!;
-      expect(reembedded.model).toBe('openai:text-embedding-3-large');
-      expect(preserved.model).toBe('voyage:voyage-3');
-    } finally {
-      resetGateway();
-    }
-  });
 });

test/embed.serial.test.ts

@@ -37,8 +37,6 @@ mock.module('../src/core/embedding.ts', () => ({
   // setPageEmbeddingSignature / invalidateStaleSignatureEmbeddings resolve to
   // null via the Proxy default, so the signature value is inert here.
   currentEmbeddingSignature: () => 'test:model:1536',
-  // #1717: embed paths stamp this label on (re)embedded chunks.
-  resolveEmbeddingModelLabel: () => 'openai:text-embedding-3-large',
 }));
 
 // Import AFTER mocking.
@@ -805,34 +803,3 @@ describe('embedAllStale --source threading (D7)', () => {
     expect((firstCallOpts as { sourceId?: string }).sourceId).toBe('media-corpus');
   });
 });
-
-// #1717: content_chunks.model must record the model that actually produced
-// each vector, not the gateway/engine default.
-describe('content_chunks.model labeling (#1717)', () => {
-  test('stamps the resolved embedding model on re-embedded chunks, preserves it on untouched chunks', async () => {
-    let upserted: any[] | undefined;
-    // Chunk 0 is stale (no embedded_at) → gets re-embedded this pass.
-    // Chunk 1 is already embedded with a DIFFERENT model → must be preserved,
-    // not relabeled to the current model.
-    const chunks = [
-      { chunk_index: 0, chunk_text: 'a', chunk_source: 'compiled_truth', embedded_at: null, model: 'zeroentropyai:zembed-1', token_count: 1 },
-      { chunk_index: 1, chunk_text: 'b', chunk_source: 'compiled_truth', embedded_at: '2026-01-01', embedding: new Float32Array(1536), model: 'voyage:voyage-3', token_count: 1 },
-    ];
-    const engine = mockEngine({
-      getPage: async () => ({ slug: 'notes/x', compiled_truth: 'a', timeline: '', source_id: 'default' }),
-      getChunks: async () => chunks,
-      upsertChunks: async (_slug: string, c: any[]) => { upserted = c; },
-      setPageEmbeddingSignature: async () => null,
-    });
-
-    await runEmbedCore(engine, { slugs: ['notes/x'] });
-
-    expect(upserted).toBeDefined();
-    const byIdx = Object.fromEntries(upserted!.map(c => [c.chunk_index, c]));
-    // Re-embedded chunk carries the model that produced its vector (was
-    // mislabeled with the default before the fix).
-    expect(byIdx[0].model).toBe('openai:text-embedding-3-large');
-    // Untouched chunk keeps its original model — no wholesale relabel.
-    expect(byIdx[1].model).toBe('voyage:voyage-3');
-  });
-});

test/import-signature-stamp.serial.test.ts

@@ -73,21 +73,4 @@ describe('importFromContent embedding_signature stamping (F1)', () => {
     await importFromContent(engine, 'concepts/unstamped', '# Unstamped\n\nbody content.', { noEmbed: true });
     expect(await signatureOf('concepts/unstamped')).toBeNull();
   });
-
-  // #1717: content_chunks.model must record the model that produced the
-  // vector (the configured gateway model), not the engine's hardcoded
-  // default. The gateway here is configured to openai:text-embedding-3-large,
-  // which differs from DEFAULT_EMBEDDING_MODEL — so this fails without the
-  // import-path model stamping.
-  test('inline embed labels content_chunks.model with the configured model (#1717)', async () => {
-    await importFromContent(engine, 'concepts/labeled', '# Labeled\n\nsome body content to chunk and embed.', {});
-    const rows = await engine.executeRaw<{ model: string }>(
-      `SELECT cc.model FROM content_chunks cc
-        JOIN pages p ON p.id = cc.page_id
-       WHERE p.slug = $1 AND p.source_id = 'default'`,
-      ['concepts/labeled'],
-    );
-    expect(rows.length).toBeGreaterThan(0);
-    for (const r of rows) expect(r.model).toBe('openai:text-embedding-3-large');
-  });
 });

test/list-pages-offset.test.ts

@@ -0,0 +1,55 @@
+import { describe, test, expect } from 'bun:test';
+import { operationsByName } from '../src/core/operations.ts';
+
+/**
+ * #2876: `gbrain list --limit` silently clamped at 100 with no pagination.
+ * list_pages now declares `offset` (both engines already supported it on
+ * PageFilters) and the limit description discloses the 100-row cap.
+ */
+describe('list_pages pagination (#2876)', () => {
+  const listPagesOp = operationsByName.list_pages;
+
+  function makeCtx(captured: unknown[]) {
+    return {
+      engine: {
+        listPages: async (filters: unknown) => {
+          captured.push(filters);
+          return [];
+        },
+      },
+      config: { engine: 'pglite' },
+      logger: { info() {}, warn() {}, error() {} },
+      dryRun: false,
+      remote: false,
+      sourceId: 'default',
+    } as any;
+  }
+
+  test('declares offset param and discloses the 100-row cap on limit', () => {
+    expect(listPagesOp.params.offset).toBeDefined();
+    expect(listPagesOp.params.offset.type).toBe('number');
+    expect(listPagesOp.params.limit.description).toContain('100');
+  });
+
+  test('threads offset through to engine.listPages', async () => {
+    const captured: any[] = [];
+    await listPagesOp.handler(makeCtx(captured), { limit: 10, offset: 30 });
+    expect(captured[0].offset).toBe(30);
+    expect(captured[0].limit).toBe(10);
+  });
+
+  test('drops negative, non-finite, and zero offsets', async () => {
+    const captured: any[] = [];
+    const ctx = makeCtx(captured);
+    await listPagesOp.handler(ctx, { offset: -5 });
+    await listPagesOp.handler(ctx, { offset: Infinity });
+    await listPagesOp.handler(ctx, { offset: 0 });
+    for (const f of captured) expect(f.offset).toBeUndefined();
+  });
+
+  test('floors fractional offsets', async () => {
+    const captured: any[] = [];
+    await listPagesOp.handler(makeCtx(captured), { offset: 7.9 });
+    expect(captured[0].offset).toBe(7);
+  });
+});