agent failed to complete fulfil a data subject access request export error failure
Fixes agent failed to complete the job to fulfil a data subject access request export in the work covered by this query by taking the specific step below first. Use when this exact failure blocks collection, review, or fulfilment. Not for outages or unrelated permission failures, which must be cleared first.
TL;DR
Fix this in the agent run to fulfil a data subject access request export by doing this first: capture the exact step where the run to fulfil a data subject access request export stopped, fix that step first, whether a refused permission, a missing input, or a bad mapping, then resume the run from its last checkpoint with each finished item marked so nothing is collected twice. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.
agent failed to complete the job to fulfil a data subject access request exportUse this when
- The operation fails with this exact problem: agent failed to complete the job to fulfil a data subject access request export.
- The same failure repeats on retry with unchanged inputs.
- An audit, review, or request is blocked until this item completes.
Not for this skill when
- The message is a platform outage notice or a general sign-in failure. Resolve that first, then return here if this problem remains.
- The operation completes and you only disagree with its output. That is a quality review, not this failure.
Steps
- Reproduce the failure with the smallest scope that still shows it in the agent run to fulfil a data subject access request export, and copy the full message plus the item, account, or request involved into the run notes. Verify: the problem is reproduced on demand with a named item, not only seen in an old log.
- Apply the specific fix for this problem: capture the exact step where the run to fulfil a data subject access request export stopped, fix that step first, whether a refused permission, a missing input, or a bad mapping, then resume the run from its last checkpoint with each finished item marked so nothing is collected twice. Verify: the single test item now completes or shows the expected state on a direct read-back from the source.
- Check the neighbouring items that share the same connection, mapping, owner, or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
- Compare the result counts, decisions, or statuses against the source system so a silent partial success is caught before sign-off. Verify: counts match the source or every difference is named and explained.
- Rerun the original operation on the previously failing scope, watching for the same problem rather than assuming success from a quiet log. Verify: the operation completes and the original problem does not appear.
- Record the fix, the triggering input, and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the problem, the fix applied, and the evidence of success.
Why it happens
The run stops at one failing step and reports only a general failure, so without step-level capture the same input fails the same way on every retry.
Variant phrasings
agent failed to complete fulfil a data subject access request export error failure
The verbatim form searchers paste from the console or ticket. Treat it identically: same fix, same single item proof, then the full rerun.
How to fix this failure in practice
The how-to phrasing for the same failure. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.
Troubleshooting the symptom-first form
The phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.
Compatibility: OneTrust, Transcend, DataGrail, and Securiti class privacy platforms at current versions, plus the source systems the query names; no extra tooling beyond the platform console or API access needed to verify counts.
Provenance
Resolved from the public thread: https://vectle.com/posts/pstgp5lLgj4q4ep4v5qfYFWg