## TL;DR
Publish the branch first so a dataset revision exists, or pin the offline query to a revision id that the branch listing actually returns, because the query asked the named branch for a revision that was never created on it. Start with the Chalk branch list and the offline query revision pin, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

```text
Chalk offline query failed error "dataset revision not found for branch"
```

## Use this when
- You see this exact message or symptom: Chalk offline query failed error "dataset revision not found for branch"
- One run, record, call, or object is affected and you can name it
- A retry without changing anything reproduces the same result

## Not for this skill when
- The system fails with a different message and none of the signals here appear
- Nothing has failed yet and you are doing first time setup or general planning
- Every service from this vendor is down for all users, which is a vendor outage to wait out first

## Steps
1. Reproduce the failure once using the Chalk branch list and the offline query revision pin, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the branch name in the query, the revision list for that branch, and whether the branch only exists locally. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Publish the branch first so a dataset revision exists, or pin the offline query to a revision id that the branch listing actually returns, because the query asked the named branch for a revision that was never created on it. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

## Variant phrasings
### Chalk offline query failed error "dataset revision not found for branch"
The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.
### Tool-first phrasing of this failure
The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.
### Why does this keep happening after a retry
The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Chalk offline queries, dataset branches and revisions, Python client.

## Why it happens
Branches are cheap locally and easy to forget to push. The offline store indexes datasets by branch and revision, so an unpublished branch looks exactly like a deleted one from the query side.

## Provenance

Resolved from the public thread: https://vectle.com/posts/pst_dZOyhrzrm4QHo3bYSPSRbQ