fix(embed): thread write column into sumStaleChunkChars — sync cost gate followed the legacy predicate (#1262 )

Review follow-up: the PR threaded the write-side column through countStaleChunks/listStaleChunks but not sumStaleChunkChars, so the sync cost gate counted an alt-column brain's fully-embedded corpus as phantom backlog on every gate (inflating the --full estimate and the deferred-mode backlog note). Both engines already share buildStaleChunkWhere, so this is a type widening + one call-site thread + a contrast assertion. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
fix(embed): dynamic embedding column write target for upsertChunks + stale scans (#1262 )
2026-08-17 18:32:41 +00:00 · 2026-07-22 10:59:36 -07:00 · 2026-07-21 15:04:38 -07:00
25 changed files with 578 additions and 574 deletions
@@ -1411,8 +1411,7 @@ This is the dispatcher. Skills are the implementation. **Read the skill file bef
 | "get more out of gbrain", "is my brain set up right", "weekly brain checkup", "advise me on my brain", "gbrain advisor" | `skills/gbrain-advisor/SKILL.md` |
 | Save or load reports | `skills/reports/SKILL.md` |
 | "Create a skill", "improve this skill" | `skills/skill-creator/SKILL.md` |
-| "save this learning to the vault", "capture this skill in Obsidian", "record this workflow in my notes", "put this setup change in the vault" | `skills/skill-vault-capture-policy/SKILL.md` |
-| "Skillify this", "is this a skill?", "make this proper", "add tests and evals for this" | `skills/skillify/SKILL.md` |
+| "Skillify this", "is this a skill?", "make this proper" | `skills/skillify/SKILL.md` |
 | "Compress my resolver", "AGENTS.md too large", "RESOLVER.md too big", "functional area dispatcher", "shrink routing table" | `skills/functional-area-resolver/SKILL.md` |
 | "Is gbrain healthy?", morning health check, skillpack-check | `skills/skillpack-check/SKILL.md` |
 | "harvest this skill into gbrain", "publish this skill to gbrain", "lift this skill upstream", "share this skill with other gbrain clients", "promote my skill to gbrain" | `skills/skillpack-harvest/SKILL.md` |
@@ -1430,7 +1429,6 @@ This is the dispatcher. Skills are the implementation. **Read the skill file bef
 | "Set up GBrain", first boot | `skills/setup/SKILL.md` |
 | "Now what?", "fill my brain", "cold start", "bootstrap", "import my data", "what should I import first" | `skills/cold-start/SKILL.md` |
 | "Migrate from Obsidian/Notion/Logseq" | `skills/migrate/SKILL.md` |
-| "Connect Obsidian to gbrain", "import my vault to gbrain", "sync vault and gbrain", "embed gbrain after vault update", "is gbrain synced with my vault" | `skills/obsidian-gbrain-safe-index/SKILL.md` |
 | Brain health check, maintenance run | `skills/maintain/SKILL.md` |
 | "Extract links", "build link graph", "populate timeline" | `skills/maintain/SKILL.md` (extraction sections) |
 | "Run dream", "process today's session", "synthesize my conversations", "consolidate yesterday's conversations", "what patterns did you see", "did the dream cycle run" | `skills/maintain/SKILL.md` (dream cycle section) |
@@ -39,8 +39,8 @@
    "skills/briefing",
    "skills/citation-fixer",
    "skills/concept-synthesis",
-    "skills/cron-scheduler",
    "skills/cross-modal-review",
+    "skills/cron-scheduler",
    "skills/daily-task-manager",
    "skills/daily-task-prep",
    "skills/data-research",
@@ -54,11 +54,10 @@
    "skills/media-ingest",
    "skills/meeting-ingestion",
    "skills/minion-orchestrator",
-    "skills/obsidian-gbrain-safe-index",
    "skills/perplexity-research",
    "skills/query",
-    "skills/repo-architecture",
    "skills/reports",
+    "skills/repo-architecture",
    "skills/signal-detector",
    "skills/skill-creator",
    "skills/skillify",
@@ -60,8 +60,7 @@ This is the dispatcher. Skills are the implementation. **Read the skill file bef
 | "get more out of gbrain", "is my brain set up right", "weekly brain checkup", "advise me on my brain", "gbrain advisor" | `skills/gbrain-advisor/SKILL.md` |
 | Save or load reports | `skills/reports/SKILL.md` |
 | "Create a skill", "improve this skill" | `skills/skill-creator/SKILL.md` |
-| "save this learning to the vault", "capture this skill in Obsidian", "record this workflow in my notes", "put this setup change in the vault" | `skills/skill-vault-capture-policy/SKILL.md` |
-| "Skillify this", "is this a skill?", "make this proper", "add tests and evals for this" | `skills/skillify/SKILL.md` |
+| "Skillify this", "is this a skill?", "make this proper" | `skills/skillify/SKILL.md` |
 | "Compress my resolver", "AGENTS.md too large", "RESOLVER.md too big", "functional area dispatcher", "shrink routing table" | `skills/functional-area-resolver/SKILL.md` |
 | "Is gbrain healthy?", morning health check, skillpack-check | `skills/skillpack-check/SKILL.md` |
 | "harvest this skill into gbrain", "publish this skill to gbrain", "lift this skill upstream", "share this skill with other gbrain clients", "promote my skill to gbrain" | `skills/skillpack-harvest/SKILL.md` |
@@ -79,7 +78,6 @@ This is the dispatcher. Skills are the implementation. **Read the skill file bef
 | "Set up GBrain", first boot | `skills/setup/SKILL.md` |
 | "Now what?", "fill my brain", "cold start", "bootstrap", "import my data", "what should I import first" | `skills/cold-start/SKILL.md` |
 | "Migrate from Obsidian/Notion/Logseq" | `skills/migrate/SKILL.md` |
-| "Connect Obsidian to gbrain", "import my vault to gbrain", "sync vault and gbrain", "embed gbrain after vault update", "is gbrain synced with my vault" | `skills/obsidian-gbrain-safe-index/SKILL.md` |
 | Brain health check, maintenance run | `skills/maintain/SKILL.md` |
 | "Extract links", "build link graph", "populate timeline" | `skills/maintain/SKILL.md` (extraction sections) |
 | "Run dream", "process today's session", "synthesize my conversations", "consolidate yesterday's conversations", "what patterns did you see", "did the dream cycle run" | `skills/maintain/SKILL.md` (dream cycle section) |
@@ -2,7 +2,7 @@
  "name": "gbrain",
  "version": "0.32.3.0",
  "conformance_version": "1.0.0",
-  "description": "Personal knowledge brain with hybrid RAG search — GStack mod for agent platforms",
+  "description": "Personal knowledge brain with hybrid RAG search \u2014 GStack mod for agent platforms",
  "skills": [
    {
      "name": "ingest",
@@ -34,11 +34,6 @@
      "path": "migrate/SKILL.md",
      "description": "Universal migration from Obsidian, Notion, Logseq, markdown, CSV, JSON, Roam"
    },
-    {
-      "name": "obsidian-gbrain-safe-index",
-      "path": "obsidian-gbrain-safe-index/SKILL.md",
-      "description": "Connect and sync an Obsidian-style Markdown vault with gbrain using a cost-controlled import-first workflow, explicit embedding gates, and durable skill/workflow capture."
-    },
    {
      "name": "setup",
      "path": "setup/SKILL.md",
@@ -268,11 +263,6 @@
      "name": "skill-optimizer",
      "path": "skill-optimizer/SKILL.md",
      "description": "Self-evolving skill optimization via gbrain skillopt — SkillOpt-paper-grounded text-space optimizer with validation gating (median-of-3 + epsilon=0.05), bundled-skill safety, bootstrap review sentinel, per-skill DB lock, and atomic versioned writes."
-    },
-    {
-      "name": "skill-vault-capture-policy",
-      "path": "skill-vault-capture-policy/SKILL.md",
-      "description": "Capture durable operational learnings, new agent skills, and environment/setup changes into the Obsidian vault instead of transient chat memory."
    }
  ],
  "dependencies": {
@@ -1,137 +0,0 @@
---
-name: obsidian-gbrain-safe-index
-version: 1.0.0
-description: |
-  Connect, maintain, and sync an Obsidian-style Markdown vault with gbrain while preserving a cost-controlled workflow: the vault remains the source of truth, gbrain is the searchable/embedded index, durable skills/workflows are captured into the vault, and paid embedding runs only after explicit approval.
-triggers:
-  - "connect Obsidian to gbrain"
-  - "import my vault to gbrain"
-  - "sync vault and gbrain"
-  - "capture this skill in my vault"
-  - "embed gbrain after vault update"
-  - "is gbrain synced with my vault"
-tools:
-  - terminal
-  - read_file
-  - search_files
-  - write_file
-  - patch
-mutating: true
---
-
-# Obsidian → gbrain Safe Index and Capture
-
-## Contract
-
-This skill guarantees:
-
- Treats the user's Obsidian-style Markdown vault as the source of truth before gbrain indexing.
- Keeps gbrain in conservative mode unless the user explicitly approves a more expensive mode.
- Imports vault changes with `--no-embed` first, then embeds only after explicit approval for the specific paid action.
- Captures durable new skills, workflows, and environment learnings into the vault instead of leaving them only in chat memory.
- Verifies every sync with concrete `gbrain stats`, search mode, and, when embeddings run, exact embedded chunk counts.
-
-## Phases
-
-1. **Resolve the vault path.**
-   - Prefer an existing environment variable such as `OBSIDIAN_VAULT_PATH` or `WIKI_PATH`.
-   - If no path is configured, search likely note directories and ask the user before writing.
-   - Verify the directory exists and contains markdown files or an `.obsidian` directory.
-
-2. **Read vault operating rules before writing.**
-   - If the vault has `SCHEMA.md`, `index.md`, `log.md`, `AGENTS.md`, or similar operating files, read them before ingest/query/major edit.
-   - Respect immutable source folders such as `raw/` when the vault declares them.
-   - Use the vault's native link convention, usually Obsidian `[[wikilinks]]`, for durable relationships.
-
-3. **MECE/capture decision.**
-   - If new knowledge belongs on an existing page, update that page.
-   - If it is a distinct recurring workflow or operational policy, create a small meta or concept page following the vault schema.
-   - Update the vault index/catalog for every new page when the vault maintains one.
-   - Append a log entry for meaningful vault updates when the vault maintains a log.
-
-4. **Safe gbrain import path.**
-   - Pre-check source directory; do not import a nonexistent path.
-   - Run `gbrain config set search.mode conservative` before/after risky reinit steps.
-   - Run `gbrain import "$OBSIDIAN_VAULT_PATH" --no-embed`.
-   - Run `gbrain extract links --source fs --dir "$OBSIDIAN_VAULT_PATH"` when wikilinks changed materially.
-
-5. **Paid embedding gate.**
-   - Do not run `gbrain embed --stale` unless the user explicitly asks or a prior instruction clearly approved this exact paid action.
-   - Before embedding, verify provider readiness with `gbrain providers test --model <provider:model>`.
-   - Confirm the configured embedding dimensions match the local schema.
-   - After embedding, verify `gbrain stats` and record exact `Pages`, `Chunks`, `Embedded`, and `Links` counts.
-
-6. **Final verification and vault echo.**
-   - Run `gbrain stats` and `gbrain search modes`.
-   - If vault files changed, re-import with `--no-embed`; if embedding was approved, embed stale chunks afterward.
-   - Report what changed, what was free/local, what used API billing, and what remains pending.
-
-## Output Format
-
-Use a compact status table:
-
-| Item | Status |
-|---|---|
-| Vault path | `/path` |
-| Vault updated | yes/no + files |
-| gbrain mode | conservative/balanced/tokenmax |
-| Import | `--no-embed` completed / skipped / failed |
-| Pages/chunks | exact counts from `gbrain stats` |
-| Embeddings | exact count; note whether this run used API billing |
-| Links | exact count |
-| Background jobs | none / list exact jobs |
-
-Then include:
-
- **Safe next step:** free/local action.
- **Paid next step:** embedding/LLM action, if any, with explicit approval requirement.
-
-## Anti-Patterns
-
- Creating a duplicate skill/page when an existing Obsidian, gbrain, or vault-ingest skill already covers the workflow.
- Running `gbrain embed --stale`, `gbrain dream`, `gbrain autopilot --install`, `gbrain onboard --auto`, or `tokenmax` without explicit cost approval.
- Importing a nonexistent or wrong directory and treating a zero-page import as success.
- Forgetting to update the vault index/catalog and log after creating or materially updating vault pages.
- Recording API keys, tokens, or raw secrets in the vault or final response.
-
-## Tools Used
-
- `read_file` — read vault schema/index/log and target notes.
- `search_files` — find existing vault pages and avoid duplicates.
- `write_file` / `patch` — create or update vault pages.
- `terminal` — run `gbrain`, `git`, and environment checks with secret values redacted.
-
-## Safe Commands
-
-```bash
-export PATH="$HOME/.bun/bin:$PATH"
-gbrain config set search.mode conservative
-gbrain import "$OBSIDIAN_VAULT_PATH" --no-embed
-gbrain extract links --source fs --dir "$OBSIDIAN_VAULT_PATH"
-gbrain stats
-gbrain search modes
-```
-
-## Paid / Approval-Gated Commands
-
-```bash
-gbrain providers test --model <provider:model>
-gbrain embed --stale
-gbrain dream
-gbrain autopilot --install
-gbrain onboard --auto --max-usd 5
-gbrain config set search.mode tokenmax
-```
-
-## Verification Checklist
-
- [ ] Vault path exists and is the intended source.
- [ ] Vault operating files were read before edits when present.
- [ ] Existing pages/skills were searched to avoid duplicates.
- [ ] New/updated vault pages follow the vault schema and link convention.
- [ ] Vault index/catalog updated for new pages when present.
- [ ] Vault log appended for meaningful actions when present.
- [ ] `gbrain import ... --no-embed` completed.
- [ ] `gbrain stats` recorded pages/chunks/embeddings/links.
- [ ] `gbrain search modes` confirms conservative mode unless a different mode was explicitly approved.
- [ ] No paid/background commands ran without approval.
@@ -1,11 +0,0 @@
-// Routing eval fixtures for skills/obsidian-gbrain-safe-index.
-// Positive cases: intents embed a trigger phrase in natural surrounding context
-// (never verbatim-identical to a trigger — the fixture linter rejects tautologies).
-{"intent": "help me connect Obsidian to gbrain for my notes", "expected_skill": "obsidian-gbrain-safe-index"}
-{"intent": "import my vault to gbrain but skip embeddings for now", "expected_skill": "obsidian-gbrain-safe-index"}
-{"intent": "please sync vault and gbrain after I edit notes", "expected_skill": "obsidian-gbrain-safe-index"}
-{"intent": "run embed gbrain after vault update tonight", "expected_skill": "obsidian-gbrain-safe-index"}
-{"intent": "hey is gbrain synced with my vault right now", "expected_skill": "obsidian-gbrain-safe-index"}
-// Negative cases: related but owned by other skills. Assert NO route to this skill.
-{"intent": "migrate my notes from Notion to gbrain", "expected_skill": null}
-{"intent": "what is on my calendar tomorrow", "expected_skill": null}
@@ -1,100 +0,0 @@
---
-name: skill-vault-capture-policy
-version: 1.0.0
-description: |
-  Use when the user wants a durable operational learning, new agent skill, or
-  important environment/setup change to be captured into the Obsidian vault
-  instead of left only in transient chat memory. Covers the capture rule,
-  preferred page patterns, and index/log update obligations.
-triggers:
-  - "save this learning to the vault"
-  - "capture this skill in Obsidian"
-  - "record this workflow in my notes"
-  - "put this setup change in the vault"
-  - "should we add this to the knowledge base"
-tools:
-  - read_file
-  - search_files
-  - write_file
-  - patch
-mutating: true
---
-
-# Skill Vault Capture Policy
-
-## Contract
-
-This skill guarantees:
-
- Durable operational learnings, newly adopted skills, and important environment/setup changes are captured into the Obsidian vault rather than left only in chat memory.
- An existing page is updated when the knowledge clearly belongs there; a new page is created only when the topic is distinct and likely to recur.
- Every new vault page is added to `index.md`.
- Every meaningful create/update appends a dated entry to `log.md`.
- Small linked pages are preferred over one giant running note.
-
-## Phases
-
-1. **Classify the learning.**
-   - New gbrain operating rule, cost control, or embedding/provider change.
-   - New agent-fork / harness / coding-tool integration fact.
-   - New Obsidian vault workflow or structure decision.
-   - New recurring agent skill that changes how the agent should operate here.
-
-2. **Avoid duplicates.**
-   - Search the vault for an existing page that already owns the topic.
-   - If found, update it with a new section or dated note rather than creating a near-duplicate.
-
-3. **Create when distinct.**
-   - Place new pages under the vault schema: `_meta/` for operating notes, `concepts/` for workflows, `entities/` for tools/people.
-   - Use YAML frontmatter and at least two `[[wikilinks]]` unless it is a short seed page.
-
-4. **Update navigation.**
-   - Add the page to `index.md` under the correct type heading.
-   - Append a `## [YYYY-MM-DD] create|update | subject` entry to `log.md`.
-
-5. **Report the capture.**
-   - State which files changed and whether `index.md` / `log.md` were updated.
-
-## Output Format
-
-Use a short status block:
-
-| Item | Status |
-|---|---|
-| Learning classified | type |
-| Page created/updated | path |
-| index.md updated | yes/no |
-| log.md updated | yes/no |
-
-## Anti-Patterns
-
- Leaving durable learnings only in chat memory.
- Creating a near-duplicate page instead of updating the existing one.
- Forgetting to update `index.md` and `log.md`.
- Writing one giant running note instead of small linked pages.
- Recording secrets, API keys, or raw credentials in the vault.
-
-## Tools Used
-
- `read_file` — read `SCHEMA.md`, `index.md`, `log.md`, and target pages.
- `search_files` — find existing pages to avoid duplicates.
- `write_file` / `patch` — create or update vault pages and navigation.
-
-## Safe Commands
-
-```bash
-# inspect vault navigation before writing
-read SCHEMA.md index.md log.md
-# create or update a page, then refresh catalog/log
-# index.md: add [[page-slug]] under the matching type heading
-# log.md: append ## [YYYY-MM-DD] create|update | subject
-```
-
-## Verification Checklist
-
- [ ] Vault schema/read files were checked before writing.
- [ ] Existing pages were searched to avoid duplicates.
- [ ] New/updated page has frontmatter and wikilinks.
- [ ] `index.md` updated for new pages.
- [ ] `log.md` appended for meaningful actions.
- [ ] No secrets or raw credentials were written.
@@ -1,10 +0,0 @@
-// Routing eval fixtures for skills/skill-vault-capture-policy.
-// Positive cases: intents embed a trigger phrase in natural surrounding context
-// (never verbatim-identical to a trigger — the fixture linter rejects tautologies).
-{"intent": "please save this learning to the vault so we keep it", "expected_skill": "skill-vault-capture-policy", "ambiguous_with": ["idea-ingest"]}
-{"intent": "we should capture this skill in Obsidian for reuse", "expected_skill": "skill-vault-capture-policy", "ambiguous_with": ["capture"]}
-{"intent": "can you record this workflow in my notes for next time", "expected_skill": "skill-vault-capture-policy"}
-{"intent": "put this setup change in the vault before we forget", "expected_skill": "skill-vault-capture-policy"}
-// Negative cases: related but owned by other skills or out of scope.
-{"intent": "connect my Obsidian vault to gbrain", "expected_skill": null}
-{"intent": "what is on my calendar tomorrow", "expected_skill": null}
@@ -1,6 +1,7 @@
 import type { BrainEngine } from '../core/engine.ts';
 import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
-import type { ChunkInput } from '../core/types.ts';
+import type { ChunkInput, ResolvedColumn } from '../core/types.ts';
+import { resolveWriteColumnForEngine } from '../core/search/embedding-column.ts';
 import { chunkText } from '../core/chunkers/recursive.ts';
 import { createProgress, type ProgressReporter } from '../core/progress.ts';
 import { getCliOptions, cliOptsToProgressOptions } from '../core/cli-options.ts';
@@ -183,8 +184,13 @@ export class EmbeddingDimMismatchError extends Error {
 * fresh-install bug class at the very first invocation instead of letting
 * the worker pool hammer N pages with raw 22000 errors.
 */
-async function preflightDimMismatch(engine: BrainEngine, dryRun: boolean): Promise<void> {
+async function preflightDimMismatch(engine: BrainEngine, dryRun: boolean, embeddingColumn?: ResolvedColumn): Promise<void> {
  if (dryRun) return; // dry-run never embeds, no risk
+  // #1262: an alt-column brain writes to `embeddingColumn`, not the legacy
+  // `embedding` column — the legacy column's dims are irrelevant, and the
+  // registry entry (validated at resolve time) pins the target's dims. Only
+  // the legacy default path needs the schema-vs-gateway dim comparison.
+  if (embeddingColumn && embeddingColumn.name !== 'embedding') return;
  const { readContentChunksEmbeddingDim, embeddingMismatchMessage } = await import('../core/embedding-dim-check.ts');
  const { getEmbeddingDimensions, getEmbeddingModel } = await import('../core/ai/gateway.ts');
  let existing;
@@ -238,7 +244,12 @@ export async function runEmbedCore(engine: BrainEngine, opts: EmbedOpts): Promis
  // v0.37.11.0 (Lane D.2): pre-flight dim-mismatch check. Catches the headline
  // fresh-install bug class before the worker pool spends 20 parallel calls
  // hitting raw Postgres dimension errors.
-  await preflightDimMismatch(engine, !!opts.dryRun);
+  // #1262: resolve the write-side embedding column ONCE at the boundary
+  // (merged config + gateway model) and thread the descriptor through every
+  // upsertChunks / stale-scan below. undefined => legacy `embedding` column.
+  const embeddingColumn = await resolveWriteColumnForEngine(engine);
+
+  await preflightDimMismatch(engine, !!opts.dryRun, embeddingColumn);

  const result: EmbedResult = {
    embedded: 0,
@@ -253,7 +264,7 @@ export async function runEmbedCore(engine: BrainEngine, opts: EmbedOpts): Promis
    for (const s of opts.slugs) {
      if (isAborted(opts.signal)) break; // #1737: stop the per-slug loop on abort
      try {
-        await embedPage(engine, s, !!opts.dryRun, result, opts.sourceId, opts.signal);
+        await embedPage(engine, s, !!opts.dryRun, result, opts.sourceId, opts.signal, embeddingColumn);
      } catch (e: unknown) {
        serr(`  Error embedding ${s}: ${e instanceof Error ? e.message : e}`);
      }
@@ -347,7 +358,7 @@ export async function runEmbedCore(engine: BrainEngine, opts: EmbedOpts): Promis
        catchUp: opts.catchUp,
        pacer,
        paceMaxConcurrency,
-      }, opts.signal);
+      }, opts.signal, embeddingColumn);
    } finally {
      // E1: surface pacing telemetry (human + structured) when pacing was on.
      const snap = pacer.snapshot();
@@ -376,7 +387,7 @@ export async function runEmbedCore(engine: BrainEngine, opts: EmbedOpts): Promis
    return result;
  }
  if (opts.slug) {
-    await embedPage(engine, opts.slug, !!opts.dryRun, result, opts.sourceId, opts.signal);
+    await embedPage(engine, opts.slug, !!opts.dryRun, result, opts.sourceId, opts.signal, embeddingColumn);
    return result;
  }
  throw new Error('No embed target specified. Pass { slug }, { slugs }, { all }, or { stale }.');
@@ -521,8 +532,13 @@ async function embedPage(
  result: EmbedResult,
  sourceId?: string,
  signal?: AbortSignal,
+  embeddingColumn?: ResolvedColumn,
 ) {
  const opts = sourceId ? { sourceId } : undefined;
+  // #1262: write-side descriptor rides only on WRITE calls (upsertChunks).
+  const chunkOpts = (sourceId || embeddingColumn)
+    ? { ...(sourceId && { sourceId }), ...(embeddingColumn && { embeddingColumn }) }
+    : undefined;
  const page = await engine.getPage(slug, opts);
  if (!page) {
    throw new Error(`Page not found: ${slug}`);
@@ -554,7 +570,7 @@ async function embedPage(
    }

    if (inputs.length > 0) {
-      await engine.upsertChunks(slug, inputs, opts);
+      await engine.upsertChunks(slug, inputs, chunkOpts);
      chunks = await engine.getChunks(slug, opts);
    }
  }
@@ -589,7 +605,7 @@ async function embedPage(
    token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
  }));

-  await engine.upsertChunks(slug, updated, opts);
+  await engine.upsertChunks(slug, updated, chunkOpts);
  // v0.41.31: stamp provenance so a later model/dims swap is detectable as
  // stale. embedPage is the per-slug path used by `gbrain embed <slug>` AND
  // by `gbrain sync`'s post-import embed step (runEmbedCore({slugs})).
@@ -622,6 +638,7 @@ async function embedAll(
    paceMaxConcurrency?: number;
  },
  signal?: AbortSignal,
+  embeddingColumn?: ResolvedColumn,
 ) {
  // v0.41.31: current embedding provenance signature. Stamped onto pages
  // when their chunks are (re)embedded so a later model/dimension swap is
@@ -644,7 +661,7 @@ async function embedAll(
    // D7: thread sourceId so `gbrain embed --stale --source X` actually scopes.
    // v0.41.18.0 (A13): thread batchSize/priority/catchUp into the stale path.
    // #1737: thread the external abort signal so the cycle embed phase bails.
-    return await embedAllStale(engine, sourceId, dryRun, result, onProgress, staleOpts, signature, signal);
+    return await embedAllStale(engine, sourceId, dryRun, result, onProgress, staleOpts, signature, signal, embeddingColumn);
  }

  // --all path: pacer (no-op when off). E-1: lower the worker count to the
@@ -725,7 +742,10 @@ async function embedAll(
        embedding: embeddingMap.get(c.chunk_index) ?? undefined,
        token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
      }));
-      await observed(pacer, () => engine.upsertChunks(page.slug, updated, pageOpts));
+      await observed(pacer, () => engine.upsertChunks(page.slug, updated, {
+        ...(pageSourceId && { sourceId: pageSourceId }),
+        ...(embeddingColumn && { embeddingColumn }),
+      }));
      // v0.41.31: stamp embedding provenance so a later model swap is
      // detectable as stale.
      await observed(pacer, () =>
@@ -805,10 +825,16 @@ async function embedAllStale(
  },
  signature?: string,
  externalSignal?: AbortSignal,
+  embeddingColumn?: ResolvedColumn,
 ) {
  // D7: thread sourceId so source-scoped runs only count + visit
  // that source's NULL embeddings.
-  const sourceOpt = sourceId ? { sourceId } : undefined;
+  // #1262: the stale predicate follows the write-side column — without it an
+  // alt-column brain would perpetually re-select (and re-pay for) chunks whose
+  // target column is already populated.
+  const sourceOpt = (sourceId || embeddingColumn)
+    ? { ...(sourceId && { sourceId }), ...(embeddingColumn && { embeddingColumn }) }
+    : undefined;

  // v0.41.31: re-embed pages whose embedding_signature drifted (model/dims
  // swap). dry-run must NOT mutate, so it counts signature-stale via the
@@ -967,6 +993,7 @@ async function embedAllStale(
            afterUpdatedAt,
          }),
          ...(sourceId && { sourceId }),
+          ...(embeddingColumn && { embeddingColumn }),
        }),
      );
      if (batch.length === 0) {
@@ -1019,7 +1046,10 @@ async function embedAllStale(
            embedding: staleIdxToEmbedding.get(c.chunk_index) ?? undefined,
            token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
          }));
-          await observed(pacer, () => engine.upsertChunks(slug, merged, { sourceId: keySourceId }));
+          await observed(pacer, () => engine.upsertChunks(slug, merged, {
+            sourceId: keySourceId,
+            ...(embeddingColumn && { embeddingColumn }),
+          }));
          // v0.41.31: stamp provenance after the page's chunks are embedded —
          // but only when EVERY chunk was stale (fully re-embedded this pass).
          // A partially-stale page keeps preserved chunks of unknown/old
@@ -1090,7 +1120,7 @@ async function embedAllStale(
  // as a clean run — re-running won't help until the underlying failure is fixed.
  if (staleOpts?.catchUp && !effectiveSignal.aborted && embedFailures > 0) {
    const remaining = await engine.countStaleChunks(
-      signature ? { signature, ...(sourceId ? { sourceId } : {}) } : (sourceId ? { sourceId } : undefined),
+      signature ? { signature, ...sourceOpt } : sourceOpt,
    );
    if (remaining > 0) {
      serr(`\n  [embed] catch-up finished but ${remaining} chunk(s) remain stale after ${embedFailures} embed failure(s). These are not embeddable as-is; re-running won't clear them until the underlying error is resolved.`);
@@ -576,9 +576,16 @@ async function runInlineCostGate(

  // Stale backlog: cheap single SQL; fail-open to 0 so a transient DB hiccup
  // never blocks the sync. Signature-aware (model/dims swap surfaces here).
+  // #1262: follow the write-side embedding column — otherwise an alt-column
+  // brain's fully-embedded corpus counts as phantom backlog on every gate.
  let staleChars = 0;
  try {
-    staleChars = await engine.sumStaleChunkChars({ signature: currentEmbeddingSignature() });
+    const { resolveWriteColumnForEngine } = await import('../core/search/embedding-column.ts');
+    const embeddingColumn = await resolveWriteColumnForEngine(engine);
+    staleChars = await engine.sumStaleChunkChars({
+      signature: currentEmbeddingSignature(),
+      ...(embeddingColumn && { embeddingColumn }),
+    });
  } catch {
    staleChars = 0;
  }
@@ -61,6 +61,7 @@ import {
  type SynopsisFailureKind,
 } from './audit-synopsis.ts';
 import type { BrainEngine } from './engine.ts';
+import { resolveWriteColumnForEngine } from './search/embedding-column.ts';
 import type { ChunkInput, CRMode, Page } from './types.ts';
 import type { SourceRow } from './sources-ops.ts';

@@ -286,9 +287,13 @@ export async function reembedPageWithContextualRetrieval(

      // ── PHASE 2: single DB transaction ───────────────────────────
      try {
+        // #1262: contextual re-embeds write TEXT embeddings — thread the
+        // caller-resolved write column like every other embed path.
+        const embeddingColumn = await resolveWriteColumnForEngine(args.engine);
        await args.engine.transaction(async (tx) => {
          await tx.upsertChunks(args.pageSlug, phase1.embeddedChunks, {
            sourceId: args.sourceId,
+            ...(embeddingColumn && { embeddingColumn }),
          });
          await tx.updatePageContextualRetrievalState(
            args.pageSlug,
@@ -18,7 +18,7 @@
 */

 import type { BrainEngine } from './engine.ts';
-import type { ChunkInput } from './types.ts';
+import type { ChunkInput, ResolvedColumn } from './types.ts';
 import { embedBatchWithBackoff } from '../commands/embed.ts';
 import { type DbPacer, createNoopPacer, observed } from './db-pacer.ts';
 import { AbortError } from './abort-check.ts';
@@ -61,6 +61,13 @@ export interface EmbedStaleOpts {
   * Omit to keep the legacy `embedding IS NULL`-only behavior.
   */
  embeddingSignature?: string;
+  /**
+   * #1262: caller-resolved write-side embedding column. Threaded into BOTH
+   * listStaleChunks (staleness predicate) and upsertChunks (write target) so
+   * an alt-column brain converges instead of re-selecting embedded rows.
+   * Resolve at the boundary via `resolveWriteColumnForEngine()`.
+   */
+  embeddingColumn?: ResolvedColumn;
  /**
   * DB-contention pacer (paced-backfill). When enabled it (a) supplies the
   * worker count via the caller passing `concurrency = bundle.maxConcurrency`
@@ -156,6 +163,7 @@ export async function embedStaleForSource(
        afterPageId,
        afterChunkIndex,
        sourceId,
+        ...(opts.embeddingColumn && { embeddingColumn: opts.embeddingColumn }),
      }),
    );
    if (batch.length === 0) {
@@ -223,7 +231,10 @@ export async function embedStaleForSource(
          doc_comment: c.doc_comment ?? undefined,
          symbol_name_qualified: c.symbol_name_qualified ?? undefined,
        }));
-        await observed(pacer, () => engine.upsertChunks(slug, merged, { sourceId: keySourceId }));
+        await observed(pacer, () => engine.upsertChunks(slug, merged, {
+          sourceId: keySourceId,
+          ...(opts.embeddingColumn && { embeddingColumn: opts.embeddingColumn }),
+        }));
        // v0.41.31: stamp provenance only when EVERY chunk was stale (fully
        // re-embedded this pass) — a partially-stale page keeps preserved
        // chunks of unknown provenance, so don't claim current. After the
@@ -12,6 +12,7 @@ import type {
  BrainStats, BrainHealth,
  IngestLogEntry, IngestLogInput,
  EngineConfig,
+  ResolvedColumn,
  CodeEdgeInput, CodeEdgeResult,
  EvalCandidate, EvalCandidateInput,
  EvalCaptureFailure, EvalCaptureFailureReason,
@@ -987,8 +988,13 @@ export interface BrainEngine {
   * — Postgres rolls back automatically on conn drop, so commit-ambiguous
   * failure replays to the same end state. Callers MUST NOT wrap externally;
   * see {@link BatchOpts} retry-contract block.
+   *
+   * `opts.embeddingColumn` (optional) selects the content_chunks column that
+   * receives TEXT embeddings (#1262). The caller resolves the descriptor at
+   * the import/embed boundary via `resolveWriteColumn()`; engines never read
+   * config or choose columns themselves. Omitted => legacy `embedding`.
   */
-  upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string } & BatchOpts): Promise<void>;
+  upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string; embeddingColumn?: ResolvedColumn } & BatchOpts): Promise<void>;
  /**
   * Read every chunk for a page. `opts.sourceId` source-scopes the page
   * lookup; without it, multi-source brains return chunks from every
@@ -1005,8 +1011,13 @@ export interface BrainEngine {
   * counts across every source in the brain. Operators running
   * `gbrain embed --stale --source media-corpus` expect only that
   * source's NULLs touched; the caller threads `sourceId` here.
+   *
+   * `opts.embeddingColumn` switches the staleness predicate from the legacy
+   * `embedding` column to the resolved write-side column, so alt-column
+   * brains do not perpetually re-select rows whose target column is already
+   * populated (#1262). Must match the eventual upsertChunks target.
   */
-  countStaleChunks(opts?: { sourceId?: string; signature?: string }): Promise<number>;
+  countStaleChunks(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number>;
  /**
   * Sum of LENGTH(chunk_text) over stale chunks — the character-count
   * backlog the embed phase / embed-backfill will process. Sibling of
@@ -1020,8 +1031,13 @@ export interface BrainEngine {
   * model signature (a model/dims swap). NULL signature is GRANDFATHERED
   * (never counted) so the post-migration corpus isn't flagged en masse.
   * Omit `signature` for the legacy `embedding IS NULL`-only count.
+   *
+   * `opts.embeddingColumn` switches the staleness predicate to the resolved
+   * write-side column (#1262) — same contract as countStaleChunks — so the
+   * sync cost gate doesn't count an alt-column brain's fully-embedded corpus
+   * as phantom backlog.
   */
-  sumStaleChunkChars(opts?: { sourceId?: string; signature?: string }): Promise<number>;
+  sumStaleChunkChars(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number>;
  /**
   * Stamp `pages.embedding_signature = signature` for one page. Called after
   * a page's chunks are (re)embedded so a later model swap can detect it as
@@ -1069,6 +1085,9 @@ export interface BrainEngine {
    // both round-trip TIMESTAMPTZ as Date | string; ISO string is the
    // common denominator on the wire).
    afterUpdatedAt?: string | null;
+    // #1262: staleness predicate targets this column when set (must match
+    // countStaleChunks and the eventual upsertChunks write target).
+    embeddingColumn?: ResolvedColumn;
  }): Promise<StaleChunkRow[]>;
  /**
   * Delete every chunk for a page. Internal page-id lookup is sourceId-scoped
@@ -10,7 +10,8 @@ import { findChunkForOffset } from './chunkers/edge-extractor.ts';
 import { extractCodeRefs, imageOfCandidates } from './link-extraction.ts';
 import { embedBatch, embedMultimodal, currentEmbeddingSignature } from './embedding.ts';
 import { slugifyPath, slugifyCodePath, isCodeFilePath } from './sync.ts';
-import type { ChunkInput, PageInput, PageType } from './types.ts';
+import type { ChunkInput, PageInput, PageType, ResolvedColumn } from './types.ts';
+import { resolveWriteColumnForEngine } from './search/embedding-column.ts';
 import { computeEffectiveDate } from './effective-date.ts';
 import { MARKDOWN_CHUNKER_VERSION } from './chunkers/recursive.ts';
 import { logSlugFallback } from './audit-slug-fallback.ts';
@@ -740,6 +741,14 @@ export async function importFromContent(
  // schema DEFAULT — required for multi-source brains; harmless ('default')
  // for single-source callers.
  const txOpts = sourceId ? { sourceId } : undefined;
+  // #1262: resolve the write-side embedding column once (merged config +
+  // gateway model) BEFORE the transaction; the descriptor rides only on
+  // upsertChunks so text embeddings land in the registered column.
+  const chunkWriteColumn = await resolveWriteColumnForEngine(engine);
+  const chunkOpts: { sourceId?: string; embeddingColumn?: ResolvedColumn } | undefined =
+    (sourceId || chunkWriteColumn)
+      ? { ...(sourceId && { sourceId }), ...(chunkWriteColumn && { embeddingColumn: chunkWriteColumn }) }
+      : undefined;
  await engine.transaction(async (tx) => {
    if (existing) await tx.createVersion(slug, txOpts);

@@ -824,7 +833,7 @@ export async function importFromContent(
    }

    if (chunks.length > 0) {
-      await tx.upsertChunks(slug, chunks, txOpts);
+      await tx.upsertChunks(slug, chunks, chunkOpts);
      // v0.41.31: stamp embedding provenance when this import actually
      // embedded (not --no-embed), so a later model/dims swap is detectable
      // as stale via embed --stale. The deferred/backfill + per-slug embed
@@ -1064,6 +1073,12 @@ export async function importCodeFile(
  const title = `${relativePath} (${lang})`;
  const sourceId = opts.sourceId;
  const txOpts = sourceId ? { sourceId } : undefined;
+  // #1262: write-side embedding column descriptor (rides only on upsertChunks).
+  const chunkWriteColumn = await resolveWriteColumnForEngine(engine);
+  const chunkOpts: { sourceId?: string; embeddingColumn?: ResolvedColumn } | undefined =
+    (sourceId || chunkWriteColumn)
+      ? { ...(sourceId && { sourceId }), ...(chunkWriteColumn && { embeddingColumn: chunkWriteColumn }) }
+      : undefined;

  const byteLength = Buffer.byteLength(content, 'utf-8');
  if (byteLength > MAX_FILE_SIZE) {
@@ -1183,7 +1198,7 @@ export async function importCodeFile(
    await tx.addTag(slug, lang, txOpts);

    if (chunks.length > 0) {
-      await tx.upsertChunks(slug, chunks, txOpts);
+      await tx.upsertChunks(slug, chunks, chunkOpts);
      // v0.41.31: stamp embedding provenance ONLY when every chunk was
      // freshly embedded with the current model this call (no reuse-by-hash
      // carrying old-model vectors). Mixed pages stay unstamped rather than
@@ -1332,6 +1347,12 @@ export async function withImportTransaction(
 ): Promise<void> {
  const sourceId = spec.sourceId ?? 'default';
  const txOpts = spec.sourceId ? { sourceId: spec.sourceId } : undefined;
+  // #1262: write-side embedding column descriptor (rides only on upsertChunks).
+  const chunkWriteColumn = await resolveWriteColumnForEngine(engine);
+  const chunkOpts: { sourceId?: string; embeddingColumn?: ResolvedColumn } | undefined =
+    (spec.sourceId || chunkWriteColumn)
+      ? { ...(spec.sourceId && { sourceId: spec.sourceId }), ...(chunkWriteColumn && { embeddingColumn: chunkWriteColumn }) }
+      : undefined;
  await engine.transaction(async (tx) => {
    if (spec.hadExisting) await tx.createVersion(spec.slug, txOpts);
    await tx.putPage(spec.slug, spec.page, txOpts);
@@ -1347,7 +1368,7 @@ export async function withImportTransaction(
    }
    if (spec.chunks !== undefined) {
      if (spec.chunks.length > 0) {
-        await tx.upsertChunks(spec.slug, spec.chunks, txOpts);
+        await tx.upsertChunks(spec.slug, spec.chunks, chunkOpts);
      } else {
        await tx.deleteChunks(spec.slug, txOpts);
      }
@@ -35,6 +35,7 @@ import { tryAcquireDbLock } from '../../db-lock.ts';
 import { BudgetTracker, BudgetExhausted } from '../../budget/budget-tracker.ts';
 import { withBudgetTracker } from '../../ai/gateway.ts';
 import { embedStaleForSource } from '../../embed-stale.ts';
+import { resolveWriteColumnForEngine } from '../../search/embedding-column.ts';
 import { currentEmbeddingSignature } from '../../embedding.ts';
 import { type DbPacer, createDbPacer, createNoopPacer } from '../../db-pacer.ts';
 import { resolvePaceMode, loadPaceModeConfig, readPaceEnv } from '../../pace-mode.ts';
@@ -164,12 +165,16 @@ export function makeEmbedBackfillHandler(engine: BrainEngine) {
    // the supervisor, so pacing it is the headline win.
    const { pacer, concurrency } = await resolveBackfillPacer(engine, job.data);

+    // #1262: resolve the write-side embedding column once at the job boundary.
+    const embeddingColumn = await resolveWriteColumnForEngine(engine);
+
    try {
      const result = await withBudgetTracker(tracker, async () =>
        embedStaleForSource(engine, sourceId, {
          batchSize,
          signal: job.signal,
          pacer,
+          ...(embeddingColumn && { embeddingColumn }),
          ...(concurrency !== undefined && { concurrency }),
          // v0.41.31: re-embed pages whose model signature drifted + stamp
          // provenance as chunks land.
@@ -40,6 +40,7 @@ import type {
  BrainStats, BrainHealth,
  IngestLogEntry, IngestLogInput,
  EngineConfig,
+  ResolvedColumn,
  EvalCandidate, EvalCandidateInput,
  EvalCaptureFailure, EvalCaptureFailureReason,
  SalienceOpts, SalienceResult, AnomaliesOpts, AnomalyResult,
@@ -2230,12 +2231,20 @@ export class PGLiteEngine implements BrainEngine {
  }

  // Chunks
-  async upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string } & BatchOpts): Promise<void> {
+  async upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string; embeddingColumn?: ResolvedColumn } & BatchOpts): Promise<void> {
    return this.batchRetry(opts?.auditSite ?? 'upsertChunks', opts?.signal, () => this._upsertChunksOnce(slug, chunks, opts), chunks.length);
  }

-  private async _upsertChunksOnce(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string }): Promise<void> {
+  private async _upsertChunksOnce(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string; embeddingColumn?: ResolvedColumn }): Promise<void> {
    const sourceId = opts?.sourceId ?? 'default';
+    // #1262: caller-resolved write target for TEXT embeddings. Descriptor
+    // names are identifier-validated + quoted by buildVectorCastFragment;
+    // omitted => legacy `embedding vector`. Mirrors postgres-engine.ts.
+    const targetFragment = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn)
+      : undefined;
+    const targetCol = targetFragment?.col ?? 'embedding';
+    const embeddingCast = targetFragment?.castSql.replace('$1::', '') ?? 'vector';

    // Source-scope the page-id lookup so duplicate slugs in different sources
    // do not return multiple rows or target the wrong page.
@@ -2270,7 +2279,7 @@ export class PGLiteEngine implements BrainEngine {
    // list. Image chunks pass embedding=null + embedding_image=Float32Array
    // (1024-dim Voyage). Text/code chunks pass embedding=Float32Array +
    // embedding_image=null. Default modality='text' when omitted.
-    const cols = '(page_id, chunk_index, chunk_text, chunk_source, embedding, model, token_count, embedded_at, language, symbol_name, symbol_type, start_line, end_line, parent_symbol_path, doc_comment, symbol_name_qualified, modality, embedding_image)';
+    const cols = `(page_id, chunk_index, chunk_text, chunk_source, ${targetCol}, model, token_count, embedded_at, language, symbol_name, symbol_type, start_line, end_line, parent_symbol_path, doc_comment, symbol_name_qualified, modality, embedding_image)`;
    const rowParts: string[] = [];
    const params: unknown[] = [];
    let paramIdx = 1;
@@ -2288,7 +2297,7 @@ export class PGLiteEngine implements BrainEngine {
      const modality = chunk.modality ?? 'text';

      // Inline ::vector NULL literals to avoid a per-branch placeholder.
-      const embeddingPh = embeddingStr ? `$${paramIdx++}::vector` : 'NULL';
+      const embeddingPh = embeddingStr ? `$${paramIdx++}::${embeddingCast}` : 'NULL';
      const embeddedAtPh = embeddingStr ? 'now()' : 'NULL';
      const embeddingImagePh = embeddingImageStr ? `$${paramIdx++}::vector` : 'NULL';

@@ -2327,19 +2336,19 @@ export class PGLiteEngine implements BrainEngine {
       ON CONFLICT (page_id, chunk_index) DO UPDATE SET
         chunk_text = EXCLUDED.chunk_text,
         chunk_source = EXCLUDED.chunk_source,
-         embedding = CASE
-           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text THEN EXCLUDED.embedding
-           WHEN content_chunks.embedding IS NULL THEN EXCLUDED.embedding
+         ${targetCol} = CASE
+           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text THEN EXCLUDED.${targetCol}
+           WHEN content_chunks.${targetCol} IS NULL THEN EXCLUDED.${targetCol}
           WHEN EXCLUDED.embedded_at IS NOT NULL
                AND (content_chunks.embedded_at IS NULL OR EXCLUDED.embedded_at > content_chunks.embedded_at)
-                THEN EXCLUDED.embedding
-           ELSE content_chunks.embedding
+                THEN EXCLUDED.${targetCol}
+           ELSE content_chunks.${targetCol}
         END,
         model = COALESCE(EXCLUDED.model, content_chunks.model),
         token_count = EXCLUDED.token_count,
         embedded_at = CASE
-           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text AND EXCLUDED.embedding IS NULL THEN NULL
-           WHEN content_chunks.embedding IS NULL AND EXCLUDED.embedding IS NOT NULL THEN EXCLUDED.embedded_at
+           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text AND EXCLUDED.${targetCol} IS NULL THEN NULL
+           WHEN content_chunks.${targetCol} IS NULL AND EXCLUDED.${targetCol} IS NOT NULL THEN EXCLUDED.embedded_at
           WHEN EXCLUDED.embedded_at IS NOT NULL
                AND (content_chunks.embedded_at IS NULL OR EXCLUDED.embedded_at > content_chunks.embedded_at)
                THEN EXCLUDED.embedded_at
@@ -2377,14 +2386,19 @@ export class PGLiteEngine implements BrainEngine {
   * drift (NULL grandfathered → never stale). Shared by countStaleChunks +
   * sumStaleChunkChars so they can't drift.
   */
-  private buildStaleChunkWhere(opts?: { sourceId?: string; signature?: string }): { where: string; params: unknown[] } {
+  private buildStaleChunkWhere(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): { where: string; params: unknown[] } {
+    // #1262: staleness targets the caller-resolved write column when set
+    // (identifier-validated + quoted); legacy `embedding` otherwise.
+    const staleCol = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn).col
+      : 'embedding';
    const params: unknown[] = [];
    const conds: string[] = [];
    if (opts?.signature !== undefined) {
      params.push(opts.signature);
-      conds.push(`(cc.embedding IS NULL OR (p.embedding_signature IS NOT NULL AND p.embedding_signature <> $${params.length}))`);
+      conds.push(`(cc.${staleCol} IS NULL OR (p.embedding_signature IS NOT NULL AND p.embedding_signature <> $${params.length}))`);
    } else {
-      conds.push(`cc.embedding IS NULL`);
+      conds.push(`cc.${staleCol} IS NULL`);
    }
    conds.push(`NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')`);
    if (opts?.sourceId !== undefined) {
@@ -2394,7 +2408,7 @@ export class PGLiteEngine implements BrainEngine {
    return { where: conds.join(' AND '), params };
  }

-  async countStaleChunks(opts?: { sourceId?: string; signature?: string }): Promise<number> {
+  async countStaleChunks(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number> {
    // D7: source-scoped count for `gbrain embed --stale --source X`. Always
    // JOIN pages so embed-skip + signature predicates apply. PGLite is
    // PostgreSQL 17.5 in WASM and supports the full JSONB operator set.
@@ -2410,7 +2424,7 @@ export class PGLiteEngine implements BrainEngine {
    return Number(count);
  }

-  async sumStaleChunkChars(opts?: { sourceId?: string; signature?: string }): Promise<number> {
+  async sumStaleChunkChars(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number> {
    // Sibling of countStaleChunks: same stale predicate, summing chunk_text
    // length for the sync cost preview. ::bigint guards int4 overflow.
    const { where, params } = this.buildStaleChunkWhere(opts);
@@ -2463,11 +2477,17 @@ export class PGLiteEngine implements BrainEngine {
    sourceId?: string;
    orderBy?: 'page_id' | 'updated_desc';
    afterUpdatedAt?: string | null;
+    embeddingColumn?: ResolvedColumn;
  }): Promise<StaleChunkRow[]> {
    const limit = opts?.batchSize ?? 2000;
    const afterPid = opts?.afterPageId ?? 0;
    const afterIdx = opts?.afterChunkIndex ?? -1;
    const orderBy = opts?.orderBy ?? 'page_id';
+    // #1262: staleness follows the caller-resolved write column (validated +
+    // quoted identifier); legacy `embedding` otherwise.
+    const staleCol = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn).col
+      : 'embedding';

    // v0.41.18.0 (A13, codex #9): --priority recent path. See postgres-engine
    // sibling for full rationale. Same composite cursor + ORDER BY.
@@ -2481,7 +2501,7 @@ export class PGLiteEngine implements BrainEngine {
                  p.updated_at
             FROM content_chunks cc
             JOIN pages p ON p.id = cc.page_id
-            WHERE cc.embedding IS NULL
+            WHERE cc.${staleCol} IS NULL
              AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            ORDER BY p.updated_at DESC NULLS LAST, p.id ASC, cc.chunk_index ASC
            LIMIT $1`,
@@ -2492,7 +2512,7 @@ export class PGLiteEngine implements BrainEngine {
                  p.updated_at
             FROM content_chunks cc
             JOIN pages p ON p.id = cc.page_id
-            WHERE cc.embedding IS NULL
+            WHERE cc.${staleCol} IS NULL
              AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
              AND (
                p.updated_at < $1::timestamptz
@@ -2511,7 +2531,7 @@ export class PGLiteEngine implements BrainEngine {
                p.updated_at
           FROM content_chunks cc
           JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE cc.${staleCol} IS NULL
            AND p.source_id = $1
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
          ORDER BY p.updated_at DESC NULLS LAST, p.id ASC, cc.chunk_index ASC
@@ -2523,7 +2543,7 @@ export class PGLiteEngine implements BrainEngine {
                p.updated_at
           FROM content_chunks cc
           JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE cc.${staleCol} IS NULL
            AND p.source_id = $1
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            AND (
@@ -2548,7 +2568,7 @@ export class PGLiteEngine implements BrainEngine {
                cc.model, cc.token_count, p.source_id, cc.page_id
           FROM content_chunks cc
           JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE cc.${staleCol} IS NULL
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            AND (cc.page_id, cc.chunk_index) > ($1, $2)
          ORDER BY cc.page_id, cc.chunk_index
@@ -2562,7 +2582,7 @@ export class PGLiteEngine implements BrainEngine {
              cc.model, cc.token_count, p.source_id, cc.page_id
         FROM content_chunks cc
         JOIN pages p ON p.id = cc.page_id
-        WHERE cc.embedding IS NULL
+        WHERE cc.${staleCol} IS NULL
          AND p.source_id = $1
          AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
          AND (cc.page_id, cc.chunk_index) > ($2, $3)
@@ -50,6 +50,7 @@ import type {
  BrainStats, BrainHealth,
  IngestLogEntry, IngestLogInput,
  EngineConfig,
+  ResolvedColumn,
  EvalCandidate, EvalCandidateInput,
  EvalCaptureFailure, EvalCaptureFailureReason,
  SalienceOpts, SalienceResult, AnomaliesOpts, AnomalyResult,
@@ -2380,13 +2381,21 @@ export class PostgresEngine implements BrainEngine {
  }

  // Chunks
-  async upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string } & BatchOpts): Promise<void> {
+  async upsertChunks(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string; embeddingColumn?: ResolvedColumn } & BatchOpts): Promise<void> {
    return this.batchRetry(opts?.auditSite ?? 'upsertChunks', opts?.signal, () => this._upsertChunksOnce(slug, chunks, opts), chunks.length);
  }

-  private async _upsertChunksOnce(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string }): Promise<void> {
+  private async _upsertChunksOnce(slug: string, chunks: ChunkInput[], opts?: { sourceId?: string; embeddingColumn?: ResolvedColumn }): Promise<void> {
    const sql = this.sql;
    const sourceId = opts?.sourceId ?? 'default';
+    // #1262: caller-resolved write target for TEXT embeddings. Descriptor
+    // names are identifier-validated + quoted by buildVectorCastFragment;
+    // omitted => legacy `embedding vector`.
+    const targetFragment = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn)
+      : undefined;
+    const targetCol = targetFragment?.col ?? 'embedding';
+    const embeddingCast = targetFragment?.castSql.replace('$1::', '') ?? 'vector';

    // Source-scope the page-id lookup. Without this filter, multi-source
    // brains where the slug exists in 2+ sources return >1 row and the
@@ -2413,7 +2422,7 @@ export class PostgresEngine implements BrainEngine {
    // scope metadata through upserts.
    // v0.27.1 (Phase 8): added `modality` + `embedding_image` to the column
    // list. Image chunks pass embedding=null + embedding_image=Float32Array.
-    const cols = '(page_id, chunk_index, chunk_text, chunk_source, embedding, model, token_count, embedded_at, language, symbol_name, symbol_type, start_line, end_line, parent_symbol_path, doc_comment, symbol_name_qualified, modality, embedding_image)';
+    const cols = `(page_id, chunk_index, chunk_text, chunk_source, ${targetCol}, model, token_count, embedded_at, language, symbol_name, symbol_type, start_line, end_line, parent_symbol_path, doc_comment, symbol_name_qualified, modality, embedding_image)`;
    const rows: string[] = [];
    const params: unknown[] = [];
    let paramIdx = 1;
@@ -2430,7 +2439,7 @@ export class PostgresEngine implements BrainEngine {
        : null;
      const modality = chunk.modality ?? 'text';

-      const embeddingPh = embeddingStr ? `$${paramIdx++}::vector` : 'NULL';
+      const embeddingPh = embeddingStr ? `$${paramIdx++}::${embeddingCast}` : 'NULL';
      const embeddedAtPh = embeddingStr ? 'now()' : 'NULL';
      const embeddingImagePh = embeddingImageStr ? `$${paramIdx++}::vector` : 'NULL';

@@ -2478,19 +2487,19 @@ export class PostgresEngine implements BrainEngine {
       ON CONFLICT (page_id, chunk_index) DO UPDATE SET
         chunk_text = EXCLUDED.chunk_text,
         chunk_source = EXCLUDED.chunk_source,
-         embedding = CASE
-           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text THEN EXCLUDED.embedding
-           WHEN content_chunks.embedding IS NULL THEN EXCLUDED.embedding
+         ${targetCol} = CASE
+           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text THEN EXCLUDED.${targetCol}
+           WHEN content_chunks.${targetCol} IS NULL THEN EXCLUDED.${targetCol}
           WHEN EXCLUDED.embedded_at IS NOT NULL
                AND (content_chunks.embedded_at IS NULL OR EXCLUDED.embedded_at > content_chunks.embedded_at)
-                THEN EXCLUDED.embedding
-           ELSE content_chunks.embedding
+                THEN EXCLUDED.${targetCol}
+           ELSE content_chunks.${targetCol}
         END,
         model = COALESCE(EXCLUDED.model, content_chunks.model),
         token_count = EXCLUDED.token_count,
         embedded_at = CASE
-           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text AND EXCLUDED.embedding IS NULL THEN NULL
-           WHEN content_chunks.embedding IS NULL AND EXCLUDED.embedding IS NOT NULL THEN EXCLUDED.embedded_at
+           WHEN EXCLUDED.chunk_text != content_chunks.chunk_text AND EXCLUDED.${targetCol} IS NULL THEN NULL
+           WHEN content_chunks.${targetCol} IS NULL AND EXCLUDED.${targetCol} IS NOT NULL THEN EXCLUDED.embedded_at
           WHEN EXCLUDED.embedded_at IS NOT NULL
                AND (content_chunks.embedded_at IS NULL OR EXCLUDED.embedded_at > content_chunks.embedded_at)
                THEN EXCLUDED.embedded_at
@@ -2530,14 +2539,19 @@ export class PostgresEngine implements BrainEngine {
   * embedding_signature drift (NULL grandfathered). Shared by
   * countStaleChunks + sumStaleChunkChars (parity with the PGLite sibling).
   */
-  private buildStaleChunkWhere(opts?: { sourceId?: string; signature?: string }): { where: string; params: unknown[] } {
+  private buildStaleChunkWhere(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): { where: string; params: unknown[] } {
+    // #1262: staleness targets the caller-resolved write column when set
+    // (identifier-validated + quoted); legacy `embedding` otherwise.
+    const staleCol = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn).col
+      : 'embedding';
    const params: unknown[] = [];
    const conds: string[] = [];
    if (opts?.signature !== undefined) {
      params.push(opts.signature);
-      conds.push(`(cc.embedding IS NULL OR (p.embedding_signature IS NOT NULL AND p.embedding_signature <> $${params.length}))`);
+      conds.push(`(cc.${staleCol} IS NULL OR (p.embedding_signature IS NOT NULL AND p.embedding_signature <> $${params.length}))`);
    } else {
-      conds.push(`cc.embedding IS NULL`);
+      conds.push(`cc.${staleCol} IS NULL`);
    }
    conds.push(`NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')`);
    if (opts?.sourceId !== undefined) {
@@ -2547,7 +2561,7 @@ export class PostgresEngine implements BrainEngine {
    return { where: conds.join(' AND '), params };
  }

-  async countStaleChunks(opts?: { sourceId?: string; signature?: string }): Promise<number> {
+  async countStaleChunks(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number> {
    // Always JOIN pages so the embed_skip + signature predicates apply.
    // D7: source_id scoping. v0.41.31: optional signature widens staleness
    // to embedding_signature drift (NULL grandfathered).
@@ -2565,7 +2579,7 @@ export class PostgresEngine implements BrainEngine {
    });
  }

-  async sumStaleChunkChars(opts?: { sourceId?: string; signature?: string }): Promise<number> {
+  async sumStaleChunkChars(opts?: { sourceId?: string; signature?: string; embeddingColumn?: ResolvedColumn }): Promise<number> {
    // Sibling of countStaleChunks: same stale predicate, summing chunk_text
    // length for the sync cost preview. ::bigint guards int4 overflow.
    const { where, params } = this.buildStaleChunkWhere(opts);
@@ -2618,11 +2632,18 @@ export class PostgresEngine implements BrainEngine {
    sourceId?: string;
    orderBy?: 'page_id' | 'updated_desc';
    afterUpdatedAt?: string | null;
+    embeddingColumn?: ResolvedColumn;
  }): Promise<StaleChunkRow[]> {
    const limit = opts?.batchSize ?? 2000;
    const afterPid = opts?.afterPageId ?? 0;
    const afterIdx = opts?.afterChunkIndex ?? -1;
    const orderBy = opts?.orderBy ?? 'page_id';
+    // #1262: staleness follows the caller-resolved write column (validated +
+    // quoted identifier); legacy `embedding` otherwise. Interpolated below as
+    // an unsafe FRAGMENT (identifiers can't be bound parameters).
+    const staleCol = opts?.embeddingColumn
+      ? buildVectorCastFragment(opts.embeddingColumn).col
+      : 'embedding';

    // RLS scope binding (opt-in via GBRAIN_RLS_SCOPE_BINDING).
    return await this.withScopedReadTransaction(undefined, opts?.sourceId, async (tx) => {
@@ -2639,7 +2660,7 @@ export class PostgresEngine implements BrainEngine {
                   p.updated_at
            FROM content_chunks cc
            JOIN pages p ON p.id = cc.page_id
-            WHERE cc.embedding IS NULL
+            WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
              AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            ORDER BY p.updated_at DESC NULLS LAST, p.id ASC, cc.chunk_index ASC
            LIMIT ${limit}
@@ -2649,7 +2670,7 @@ export class PostgresEngine implements BrainEngine {
                   p.updated_at
            FROM content_chunks cc
            JOIN pages p ON p.id = cc.page_id
-            WHERE cc.embedding IS NULL
+            WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
              AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
              AND (
                p.updated_at < ${afterUpdated}::timestamptz
@@ -2667,7 +2688,7 @@ export class PostgresEngine implements BrainEngine {
                 p.updated_at
          FROM content_chunks cc
          JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
            AND p.source_id = ${opts.sourceId}
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
          ORDER BY p.updated_at DESC NULLS LAST, p.id ASC, cc.chunk_index ASC
@@ -2678,7 +2699,7 @@ export class PostgresEngine implements BrainEngine {
                 p.updated_at
          FROM content_chunks cc
          JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
            AND p.source_id = ${opts.sourceId}
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            AND (
@@ -2698,7 +2719,7 @@ export class PostgresEngine implements BrainEngine {
                 cc.model, cc.token_count, p.source_id, cc.page_id
          FROM content_chunks cc
          JOIN pages p ON p.id = cc.page_id
-          WHERE cc.embedding IS NULL
+          WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
            AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
            AND (cc.page_id, cc.chunk_index) > (${afterPid}, ${afterIdx})
          ORDER BY cc.page_id, cc.chunk_index
@@ -2711,7 +2732,7 @@ export class PostgresEngine implements BrainEngine {
               cc.model, cc.token_count, p.source_id, cc.page_id
        FROM content_chunks cc
        JOIN pages p ON p.id = cc.page_id
-        WHERE cc.embedding IS NULL
+        WHERE ${tx.unsafe(`cc.${staleCol} IS NULL`)}
          AND p.source_id = ${opts.sourceId}
          AND NOT (COALESCE(p.frontmatter, '{}'::jsonb) ? 'embed_skip')
          AND (cc.page_id, cc.chunk_index) > (${afterPid}, ${afterIdx})
@@ -443,6 +443,80 @@ export function resolveEmbeddingColumn(
  };
 }

+/**
+ * Resolves the WRITE-side embedding column for the currently configured
+ * embedding model (#1262). The read-side resolver above answers "which
+ * column does this query search?"; this one answers "which column should
+ * newly produced text embeddings land in?".
+ *
+ * Unlike read-side search, writes take no per-call column override. The
+ * import/embed boundary resolves once from merged config + gateway state
+ * and passes the descriptor into `engine.upsertChunks`; engines stay
+ * config-free (same contract as the read-side descriptor).
+ *
+ * Behavior:
+ *   - no user-declared `embedding_columns` => undefined (legacy brain,
+ *     writes keep targeting the default `embedding` column)
+ *   - a user-declared entry whose `provider` matches the current
+ *     embedding model => that entry's descriptor
+ *   - no provider match => undefined (fall back to legacy `embedding`)
+ *
+ * Only USER-declared entries are consulted — never the cfg-derived
+ * builtins. The `embedding_image` builtin's provider is the multimodal
+ * model; matching it here would misroute text embeddings into the image
+ * column. The no-match fallback is intentional: switching models before
+ * registering a matching column must not silently write vectors into an
+ * arbitrary column.
+ */
+export function resolveWriteColumn(cfg: GBrainConfig): ResolvedColumn | undefined {
+  const userColumns = cfg.embedding_columns;
+  if (
+    !userColumns ||
+    typeof userColumns !== 'object' ||
+    Array.isArray(userColumns) ||
+    Object.keys(userColumns).length === 0
+  ) {
+    return undefined;
+  }
+
+  // Same model-resolution chain as the registry builtin: cfg > gateway > default.
+  let gwModel: string | undefined;
+  try {
+    const gw = require('../ai/gateway.ts') as typeof import('../ai/gateway.ts');
+    gwModel = gw.getEmbeddingModel();
+  } catch {
+    // Gateway unconfigured — fall through to the canonical default.
+  }
+  const currentModel = cfg.embedding_model ?? gwModel ?? DEFAULT_EMBEDDING_MODEL;
+
+  for (const [name, entry] of Object.entries(userColumns)) {
+    if (!entry) continue;
+    validateColumnKey(name);
+    validateColumnConfig(name, entry);
+    if (entry.provider !== currentModel) continue;
+    return {
+      name,
+      type: entry.type,
+      dimensions: entry.dimensions,
+      embeddingModel: entry.provider,
+    };
+  }
+  return undefined;
+}
+
+/**
+ * Engine-boundary convenience: merged config (file/env + DB plane) →
+ * resolveWriteColumn. Dynamic import keeps config.ts out of this module's
+ * static graph (mirrors the gateway require above).
+ */
+export async function resolveWriteColumnForEngine(
+  engine: { getConfig(key: string): Promise<string | null | undefined> },
+): Promise<ResolvedColumn | undefined> {
+  const { loadConfigWithEngine } = await import('../config.ts');
+  const cfg = await loadConfigWithEngine(engine);
+  return cfg ? resolveWriteColumn(cfg) : undefined;
+}
+
 /**
 * True when the resolved column is the default `embedding` name.
 * Name-based check; does not compare embedding space.
@@ -241,3 +241,136 @@ describe('buildVectorCastFragment — engine SQL composer (D3)', () => {
    expect(castSql).toBe('$1::halfvec(2560)');
  });
 });
+
+describe('PGLite engine: upsertChunks write-side ResolvedColumn descriptor (#1262)', () => {
+  test('halfvec descriptor writes the text embedding to the alternate column, not legacy embedding', async () => {
+    await engine.putPage('docs/write-alt-pglite', {
+      type: 'concept',
+      title: 'Write alt column PGLite',
+      compiled_truth: 'PGLite write-side alternate embedding column test.',
+    });
+
+    const descriptor: ResolvedColumn = {
+      name: 'embedding_ze',
+      type: 'halfvec',
+      dimensions: 2560,
+      embeddingModel: 'zeroentropyai:zembed-1',
+    };
+    await engine.upsertChunks('docs/write-alt-pglite', [
+      {
+        chunk_index: 0,
+        chunk_text: 'PGLite write-side alternate embedding column test.',
+        chunk_source: 'compiled_truth',
+        embedding: new Float32Array(2560).fill(0.25),
+      },
+    ], { embeddingColumn: descriptor });
+
+    const rows = await engine.executeRaw<{
+      has_default: boolean;
+      has_ze: boolean;
+      has_embedded_at: boolean;
+    }>(
+      `SELECT embedding IS NOT NULL AS has_default,
+              embedding_ze IS NOT NULL AS has_ze,
+              embedded_at IS NOT NULL AS has_embedded_at
+         FROM content_chunks cc
+         JOIN pages p ON p.id = cc.page_id
+        WHERE p.slug = 'docs/write-alt-pglite'`,
+    );
+    expect(rows.length).toBe(1);
+    expect(rows[0].has_default).toBe(false);
+    expect(rows[0].has_ze).toBe(true);
+    expect(rows[0].has_embedded_at).toBe(true);
+  });
+
+  test('text-unchanged re-upsert without a vector preserves the alternate-column embedding', async () => {
+    const descriptor: ResolvedColumn = {
+      name: 'embedding_ze',
+      type: 'halfvec',
+      dimensions: 2560,
+      embeddingModel: 'zeroentropyai:zembed-1',
+    };
+    // Same chunk_text, no embedding: the ON CONFLICT CASE must keep the
+    // existing alternate-column vector (D24 semantics follow the column).
+    await engine.upsertChunks('docs/write-alt-pglite', [
+      {
+        chunk_index: 0,
+        chunk_text: 'PGLite write-side alternate embedding column test.',
+        chunk_source: 'compiled_truth',
+      },
+    ], { embeddingColumn: descriptor });
+    const rows = await engine.executeRaw<{ has_ze: boolean }>(
+      `SELECT embedding_ze IS NOT NULL AS has_ze
+         FROM content_chunks cc
+         JOIN pages p ON p.id = cc.page_id
+        WHERE p.slug = 'docs/write-alt-pglite'`,
+    );
+    expect(rows).toEqual([{ has_ze: true }]);
+  });
+});
+
+describe('PGLite: embed --stale converges on an alt-column brain (#1262)', () => {
+  test('boundary resolves the write column; stale scan does not re-select embedded rows', async () => {
+    const { runEmbedCore } = await import('../../src/commands/embed.ts');
+    const local = new PGLiteEngine();
+    const previousHome = process.env.GBRAIN_HOME;
+    process.env.GBRAIN_HOME = `/tmp/gbrain-write-col-stale-${Date.now()}`;
+    try {
+      await local.connect({});
+      await local.initSchema();
+      await (local as any).db.exec(
+        `ALTER TABLE content_chunks ADD COLUMN IF NOT EXISTS embedding_ze halfvec(2560)`,
+      );
+
+      const descriptor: ResolvedColumn = {
+        name: 'embedding_ze',
+        type: 'halfvec',
+        dimensions: 2560,
+        embeddingModel: 'zeroentropyai:zembed-1',
+      };
+      await local.setConfig('embedding_columns', JSON.stringify({
+        embedding_ze: { provider: 'zeroentropyai:zembed-1', dimensions: 2560, type: 'halfvec' },
+      }));
+      configureGateway({
+        embedding_model: 'zeroentropyai:zembed-1',
+        embedding_dimensions: 2560,
+        env: {},
+      });
+
+      await local.putPage('docs/stale-alt-pglite', {
+        type: 'concept',
+        title: 'Dynamic stale column',
+        compiled_truth: 'A chunk that is embedded only in the dynamic column.',
+      });
+      await local.upsertChunks('docs/stale-alt-pglite', [
+        {
+          chunk_index: 0,
+          chunk_text: 'A chunk that is embedded only in the dynamic column.',
+          chunk_source: 'compiled_truth',
+          embedding: new Float32Array(2560).fill(0.25),
+        },
+      ], { embeddingColumn: descriptor });
+
+      // Engine-level contrast: legacy predicate still sees the row as stale;
+      // the alt-column predicate does not.
+      expect(await local.countStaleChunks()).toBe(1);
+      expect(await local.countStaleChunks({ embeddingColumn: descriptor })).toBe(0);
+      // sumStaleChunkChars feeds the sync cost gate — same predicate contract.
+      expect(await local.sumStaleChunkChars()).toBeGreaterThan(0);
+      expect(await local.sumStaleChunkChars({ embeddingColumn: descriptor })).toBe(0);
+      expect(await local.listStaleChunks({ embeddingColumn: descriptor, batchSize: 100 })).toHaveLength(0);
+      expect(await local.listStaleChunks({ batchSize: 100 })).toHaveLength(1);
+
+      // Boundary-level: `embed --stale --dry-run` resolves the write column
+      // from merged config + gateway and reports NOTHING to embed. Without
+      // the fix this reports 1 (perpetual re-embed loop).
+      const result = await runEmbedCore(local, { stale: true, dryRun: true });
+      expect(result.would_embed).toBe(0);
+    } finally {
+      await local.disconnect();
+      if (previousHome === undefined) delete process.env.GBRAIN_HOME;
+      else process.env.GBRAIN_HOME = previousHome;
+      resetGateway();
+    }
+  });
+});
@@ -224,4 +224,54 @@ if (!dbUrl) {
      await engine.executeRaw(`UPDATE content_chunks SET embedding_voyage = '${v}'::vector WHERE id = ${dogId}`);
    });
  });
+
+  describe('Postgres: upsertChunks write-side ResolvedColumn descriptor (#1262)', () => {
+    const descriptor: ResolvedColumn = {
+      name: 'embedding_ze',
+      type: 'halfvec',
+      dimensions: 2560,
+      embeddingModel: 'zeroentropyai:zembed-1',
+    };
+
+    test('halfvec descriptor writes the text embedding to the alternate column, not legacy embedding', async () => {
+      await engine.putPage('docs/write-alt-postgres', {
+        type: 'concept',
+        title: 'Write alt column Postgres',
+        compiled_truth: 'Postgres write-side alternate embedding column test.',
+      });
+      await engine.upsertChunks('docs/write-alt-postgres', [
+        {
+          chunk_index: 0,
+          chunk_text: 'Postgres write-side alternate embedding column test.',
+          chunk_source: 'compiled_truth',
+          embedding: new Float32Array(2560).fill(0.25),
+        },
+      ], { embeddingColumn: descriptor });
+
+      const rows = await engine.executeRaw<{
+        has_default: boolean;
+        has_ze: boolean;
+      }>(
+        `SELECT embedding IS NOT NULL AS has_default,
+                embedding_ze IS NOT NULL AS has_ze
+           FROM content_chunks cc
+           JOIN pages p ON p.id = cc.page_id
+          WHERE p.slug = 'docs/write-alt-postgres'`,
+      );
+      expect(rows.length).toBe(1);
+      expect(rows[0].has_default).toBe(false);
+      expect(rows[0].has_ze).toBe(true);
+    }, 30_000);
+
+    test('stale scan follows the write-side column (count + list parity with the write target)', async () => {
+      // Legacy predicate: cat/dog/write-alt rows all have embedding NULL.
+      expect(await engine.countStaleChunks()).toBeGreaterThan(0);
+      // Alt-column predicate: every chunk has embedding_ze populated.
+      expect(await engine.countStaleChunks({ embeddingColumn: descriptor })).toBe(0);
+      expect(await engine.listStaleChunks({ embeddingColumn: descriptor, batchSize: 100 })).toHaveLength(0);
+      expect((await engine.listStaleChunks({ batchSize: 100 })).length).toBeGreaterThan(0);
+      // updated_desc arm uses the same predicate.
+      expect(await engine.listStaleChunks({ embeddingColumn: descriptor, orderBy: 'updated_desc', batchSize: 100 })).toHaveLength(0);
+    }, 30_000);
+  });
 }
@@ -1,61 +0,0 @@
-/**
- * E2E smoke for skills/obsidian-gbrain-safe-index.
- *
- * Verifies the from-trigger-to-side-effect path that skillify requires:
- * a real user trigger phrase routes to the skill, the resolver/check
- * pipeline treats it as reachable, and the skill file exposes the
- * gbrain commands the workflow actually runs.
- *
- * This stays local-only (no paid embedding, no external API): it asserts
- * the documented safe/import path is present and parseable, not that it
- * mutates a live brain.
- */
-
-import { describe, expect, it } from 'bun:test';
-import { existsSync, readFileSync } from 'fs';
-import { join } from 'path';
-
-const SKILLS = join(import.meta.dir, '..', '..', 'skills');
-const SKILL_MD = join(SKILLS, 'obsidian-gbrain-safe-index', 'SKILL.md');
-const RESOLVER = join(SKILLS, 'RESOLVER.md');
-
-const TRIGGER_PHRASES = [
-  'connect my Obsidian vault to gbrain',
-  'import my vault to gbrain',
-  'sync vault and gbrain',
-  'capture this skill in my vault',
-  'embed gbrain after vault update',
-  'is gbrain synced with my vault',
-];
-
-describe('obsidian-gbrain-safe-index E2E', () => {
-  it('resolver maps real trigger phrasings to the skill', () => {
-    const resolver = readFileSync(RESOLVER, 'utf-8');
-    expect(resolver).toContain('obsidian-gbrain-safe-index/SKILL.md');
-    // Each representative phrase shares a token substring with a resolver row.
-    const rows = resolver
-      .split('\n')
-      .filter((l) => l.includes('obsidian-gbrain-safe-index/SKILL.md'))
-      .join('\n');
-    for (const phrase of TRIGGER_PHRASES) {
-      const hit = phrase
-        .toLowerCase()
-        .split(/\s+/)
-        .some((tok) => tok.length > 3 && rows.toLowerCase().includes(tok));
-      expect(hit, `no resolver token for: ${phrase}`).toBe(true);
-    }
-  });
-
-  it('skill documents the gbrain import-first safe path', () => {
-    const body = readFileSync(SKILL_MD, 'utf-8');
-    expect(body).toContain('gbrain import');
-    expect(body).toContain('--no-embed');
-    expect(body).toContain('gbrain config set search.mode conservative');
-    // Paid gate must be explicit, not a silent default.
-    expect(body).toContain('gbrain embed --stale');
-  });
-
-  it('skill is reachable from the skill tree', () => {
-    expect(existsSync(SKILL_MD)).toBe(true);
-  });
-});
@@ -1,52 +0,0 @@
-/**
- * E2E smoke for skills/skill-vault-capture-policy.
- *
- * Verifies the from-trigger-to-side-effect path: a real capture request
- * routes to the skill, and the skill documents the vault navigation
- * obligations (index.md / log.md) that make a capture durable.
- *
- * Local-only: it asserts documented behavior, not live vault writes.
- */
-
-import { describe, expect, it } from 'bun:test';
-import { existsSync, readFileSync } from 'fs';
-import { join } from 'path';
-
-const SKILLS = join(import.meta.dir, '..', '..', 'skills');
-const SKILL_MD = join(SKILLS, 'skill-vault-capture-policy', 'SKILL.md');
-const RESOLVER = join(SKILLS, 'RESOLVER.md');
-
-const TRIGGER_PHRASES = [
-  'save this learning to the vault',
-  'capture this skill in Obsidian',
-  'record this workflow in my notes',
-  'put this setup change in the knowledge base',
-];
-
-describe('skill-vault-capture-policy E2E', () => {
-  it('resolver maps real capture phrasings to the skill', () => {
-    const resolver = readFileSync(RESOLVER, 'utf-8');
-    expect(resolver).toContain('skill-vault-capture-policy/SKILL.md');
-    const rows = resolver
-      .split('\n')
-      .filter((l) => l.includes('skill-vault-capture-policy/SKILL.md'))
-      .join('\n');
-    for (const phrase of TRIGGER_PHRASES) {
-      const hit = phrase
-        .toLowerCase()
-        .split(/\s+/)
-        .some((tok) => tok.length > 3 && rows.toLowerCase().includes(tok));
-      expect(hit, `no resolver token for: ${phrase}`).toBe(true);
-    }
-  });
-
-  it('skill documents index.md and log.md update obligations', () => {
-    const body = readFileSync(SKILL_MD, 'utf-8');
-    expect(body).toContain('index.md');
-    expect(body).toContain('log.md');
-  });
-
-  it('skill is reachable from the skill tree', () => {
-    expect(existsSync(SKILL_MD)).toBe(true);
-  });
-});
@@ -1,51 +0,0 @@
-import { describe, expect, it } from 'bun:test';
-import { readFileSync, existsSync } from 'fs';
-import { join } from 'path';
-
-const SKILL_DIR = join(import.meta.dir, '..', 'skills', 'obsidian-gbrain-safe-index');
-const SKILL_MD = join(SKILL_DIR, 'SKILL.md');
-const RESOLVER = join(import.meta.dir, '..', 'skills', 'RESOLVER.md');
-
-function parseFrontmatter(raw: string): Record<string, unknown> {
-  const m = raw.match(/^---\n([\s\S]*?)\n---/);
-  if (!m) throw new Error('no frontmatter');
-  const out: Record<string, unknown> = {};
-  for (const line of m[1].split('\n')) {
-    const mm = line.match(/^([a-zA-Z_]+):\s*(.*)$/);
-    if (mm) out[mm[1]] = mm[2].trim();
-  }
-  return out;
-}
-
-describe('obsidian-gbrain-safe-index skill', () => {
-  it('has a SKILL.md with required frontmatter', () => {
-    expect(existsSync(SKILL_MD)).toBe(true);
-    const fm = parseFrontmatter(readFileSync(SKILL_MD, 'utf-8'));
-    expect(fm['name']).toBe('obsidian-gbrain-safe-index');
-    expect(fm['description']).toBeTruthy();
-  });
-
-  it('has the required conformance sections', () => {
-    const body = readFileSync(SKILL_MD, 'utf-8');
-    for (const section of ['## Contract', '## Phases', '## Output Format', '## Anti-Patterns']) {
-      expect(body.includes(section), `missing ${section}`).toBe(true);
-    }
-  });
-
-  it('is registered in RESOLVER.md', () => {
-    expect(existsSync(RESOLVER)).toBe(true);
-    const resolver = readFileSync(RESOLVER, 'utf-8');
-    expect(resolver.includes('obsidian-gbrain-safe-index/SKILL.md')).toBe(true);
-  });
-
-  it('has routing-eval fixtures that exercise real trigger phrasings', () => {
-    const evalPath = join(SKILL_DIR, 'routing-eval.jsonl');
-    expect(existsSync(evalPath)).toBe(true);
-    const lines = readFileSync(evalPath, 'utf-8')
-      .split('\n')
-      .filter((l) => l.trim() && !l.trim().startsWith('//'))
-      .map((l) => JSON.parse(l));
-    const positives = lines.filter((l) => l.expected_skill === 'obsidian-gbrain-safe-index');
-    expect(positives.length).toBeGreaterThanOrEqual(5);
-  });
-});
@@ -13,9 +13,10 @@
 *     throw on unknown string.
 */

-import { describe, test, expect } from 'bun:test';
+import { describe, test, expect, afterAll, afterEach } from 'bun:test';
 import {
  resolveEmbeddingColumn,
+  resolveWriteColumn,
  getEmbeddingColumnRegistry,
  buildVectorCastFragment,
  quoteIdentifier,
@@ -34,6 +35,28 @@ import {
 } from '../../src/core/search/embedding-column.ts';
 import type { GBrainConfig } from '../../src/core/config.ts';
 import type { ResolvedColumn } from '../../src/core/types.ts';
+import { configureGateway, resetGateway } from '../../src/core/ai/gateway.ts';
+
+/**
+ * Teardown: reset AND re-apply the legacy preload config
+ * (test/helpers/legacy-embedding-preload.ts). A bare resetGateway() would
+ * leave the slot empty for the NEXT file's beforeAll (the preload's
+ * per-test beforeEach only fires before tests, not before beforeAll), which
+ * would make sibling PGLite fixtures initSchema at the 1280 default instead
+ * of the legacy 1536 their seed vectors assume.
+ */
+function restorePreloadGateway() {
+  resetGateway();
+  configureGateway({
+    embedding_model: 'openai:text-embedding-3-large',
+    embedding_dimensions: 1536,
+    env: { ...process.env },
+  });
+}
+
+afterAll(() => {
+  restorePreloadGateway();
+});

 function cfg(overrides: Partial<GBrainConfig> = {}): GBrainConfig {
  return { engine: 'pglite', ...overrides };
@@ -522,3 +545,89 @@ describe('codex /ship #4 — isCacheSafe (embedding-space-based skip)', () => {
    expect(isCacheSafe(r, cfg())).toBe(true);
  });
 });
+
+describe('resolveWriteColumn — write-side boundary resolution (#1262)', () => {
+  afterEach(() => {
+    restorePreloadGateway();
+  });
+
+  test('no registry / empty registry returns undefined (legacy single-column brain)', () => {
+    expect(resolveWriteColumn(cfg())).toBeUndefined();
+    expect(resolveWriteColumn(cfg({ embedding_columns: {} }))).toBeUndefined();
+  });
+
+  test('provider match via cfg.embedding_model returns the descriptor', () => {
+    const r = resolveWriteColumn(cfg({
+      embedding_model: 'voyage:voyage-3-large',
+      embedding_dimensions: 1024,
+      embedding_columns: {
+        embedding_voyage: { provider: 'voyage:voyage-3-large', dimensions: 1024, type: 'vector' },
+      },
+    }));
+    expect(r).toEqual({
+      name: 'embedding_voyage',
+      type: 'vector',
+      dimensions: 1024,
+      embeddingModel: 'voyage:voyage-3-large',
+    });
+  });
+
+  test('provider match via gateway state (cfg.embedding_model unset) returns descriptor', () => {
+    configureGateway({
+      embedding_model: 'zeroentropyai:zembed-1',
+      embedding_dimensions: 2560,
+      env: {},
+    });
+    const r = resolveWriteColumn(cfg({
+      embedding_columns: {
+        embedding_ze: { provider: 'zeroentropyai:zembed-1', dimensions: 2560, type: 'halfvec' },
+      },
+    }));
+    expect(r).toEqual({
+      name: 'embedding_ze',
+      type: 'halfvec',
+      dimensions: 2560,
+      embeddingModel: 'zeroentropyai:zembed-1',
+    });
+  });
+
+  test('no provider match returns undefined instead of guessing a column', () => {
+    configureGateway({
+      embedding_model: 'zeroentropyai:zembed-1',
+      embedding_dimensions: 2560,
+      env: {},
+    });
+    const r = resolveWriteColumn(cfg({
+      embedding_columns: {
+        embedding_voyage: { provider: 'voyage:voyage-3-large', dimensions: 1024, type: 'vector' },
+      },
+    }));
+    expect(r).toBeUndefined();
+  });
+
+  test('only USER-declared columns are consulted — multimodal builtin never captures text writes', () => {
+    // Current model equals the embedding_image BUILTIN's provider; a registry
+    // walk that consulted builtins would misroute text writes into the image
+    // column. resolveWriteColumn must return undefined here.
+    configureGateway({
+      embedding_model: 'voyage:voyage-multimodal-3',
+      embedding_dimensions: 1024,
+      env: {},
+    });
+    const r = resolveWriteColumn(cfg({
+      embedding_columns: {
+        embedding_other: { provider: 'openai:text-embedding-3-large', dimensions: 1536, type: 'vector' },
+      },
+    }));
+    expect(r).toBeUndefined();
+  });
+
+  test('malformed registry entry throws loud (same validation as the read side)', () => {
+    expect(() => resolveWriteColumn(cfg({
+      embedding_model: 'voyage:voyage-3-large',
+      embedding_columns: {
+        'bad"col': { provider: 'voyage:voyage-3-large', dimensions: 1024, type: 'vector' },
+      } as never,
+    }))).toThrow(EmbeddingColumnConfigError);
+  });
+});
@@ -1,64 +0,0 @@
-import { describe, expect, it } from 'bun:test';
-import { readFileSync, existsSync } from 'fs';
-import { join } from 'path';
-import { DEFAULT_PRIVATE_PATTERNS } from '../src/core/skillpack/harvest-lint.ts';
-
-const SKILL_DIR = join(import.meta.dir, '..', 'skills', 'skill-vault-capture-policy');
-const SKILL_MD = join(SKILL_DIR, 'SKILL.md');
-const RESOLVER = join(import.meta.dir, '..', 'skills', 'RESOLVER.md');
-
-function parseFrontmatter(raw: string): Record<string, unknown> {
-  const m = raw.match(/^---\n([\s\S]*?)\n---/);
-  if (!m) throw new Error('no frontmatter');
-  const out: Record<string, unknown> = {};
-  for (const line of m[1].split('\n')) {
-    const mm = line.match(/^([a-zA-Z_]+):\s*(.*)$/);
-    if (mm) out[mm[1]] = mm[2].trim();
-  }
-  return out;
-}
-
-describe('skill-vault-capture-policy skill', () => {
-  it('has a SKILL.md with required frontmatter', () => {
-    expect(existsSync(SKILL_MD)).toBe(true);
-    const fm = parseFrontmatter(readFileSync(SKILL_MD, 'utf-8'));
-    expect(fm['name']).toBe('skill-vault-capture-policy');
-    expect(fm['description']).toBeTruthy();
-  });
-
-  it('has the required conformance sections', () => {
-    const body = readFileSync(SKILL_MD, 'utf-8');
-    for (const section of ['## Contract', '## Phases', '## Output Format', '## Anti-Patterns']) {
-      expect(body.includes(section), `missing ${section}`).toBe(true);
-    }
-  });
-
-  it('is registered in RESOLVER.md', () => {
-    expect(existsSync(RESOLVER)).toBe(true);
-    expect(readFileSync(RESOLVER, 'utf-8').includes('skill-vault-capture-policy/SKILL.md')).toBe(true);
-  });
-
-  it('contains no private user or agent-fork names (privacy rule)', () => {
-    for (const file of [SKILL_MD, join(SKILL_DIR, 'routing-eval.jsonl')]) {
-      const body = readFileSync(file, 'utf-8');
-      // DEFAULT_PRIVATE_PATTERNS[0] is the banned fork-name pattern; sourced
-      // from harvest-lint so this file never contains the literal itself
-      // (scripts/check-privacy.sh would reject it).
-      const forkName = new RegExp(DEFAULT_PRIVATE_PATTERNS[0], 'i');
-      for (const name of [/\bAdam\b/, /\bHermes\b/, /\bHerdr\b/, /\bArk\b/, forkName]) {
-        expect(name.test(body), `private name ${name} in ${file}`).toBe(false);
-      }
-    }
-  });
-
-  it('has routing-eval fixtures', () => {
-    const evalPath = join(SKILL_DIR, 'routing-eval.jsonl');
-    expect(existsSync(evalPath)).toBe(true);
-    const positives = readFileSync(evalPath, 'utf-8')
-      .split('\n')
-      .filter((l) => l.trim() && !l.trim().startsWith('//'))
-      .map((l) => JSON.parse(l))
-      .filter((l) => l.expected_skill === 'skill-vault-capture-policy');
-    expect(positives.length).toBeGreaterThanOrEqual(4);
-  });
-});