agent loop detected: re-triggering failed dag run over and over

Not specified by the original author.

TL;DR

Re-triggering a deterministically failing DAG run is the definition of insanity with extra steps: the same code on the same data fails the same way. After two identical failures, stop triggering and read the failure. Fix the cause, then trigger once to verify. Triggers are for new attempts after a fix, not for hoping.

agent loop detected: re-triggering failed dag run over and over

Use this when

• An agent re-triggers a failed DAG run repeatedly.
• Each attempt fails the same way.
• No fix was applied between attempts.

Not for this skill when

• A fix was applied between attempts. That is verification, not a loop.
• Different runs fail differently. That is flakiness, not determinism.

Steps

1. Compare the failure across attempts: same task, same error. Note the match. Verify: determinism is proven
2. Stop triggering. Note the halt. Verify: the loop breaks
3. Read the failing task's logs and identify the root cause. Note the cause. Verify: the diagnosis replaces the hoping
4. Apply the fix: code, config, or data. Note the change. Verify: something actually changes
5. Trigger once and confirm the run succeeds. Note the green run. Verify: the fix is verified with one trigger

Variant phrasings

agent retrying failed dag run loop

The paraphrase.

stop re-triggering airflow dag

The fix phrasing.

Compatibility: Airflow 2.x DAG run triggering via UI, API, or CLI. Loop-breaking is agent behavior.

Why it happens

Re-triggering feels like doing something, which is why agents do it: the action is available, the failure is unexplained, and trying again is the path of least resistance. But a deterministic failure has no randomness to overcome, so each retry is pure cost: compute, time, and possibly duplicated side effects. The two-identical-failures rule is the circuit breaker. It forces the agent to spend its budget on the one thing that can help: understanding the failure.

Edge cases / pitfalls

• Re-triggering can double-apply non-idempotent tasks. The loop is not just wasteful; it can corrupt data.
• A run that fails differently each time may be flaky infrastructure, where retries are legitimate. Distinguish first.
• Clearing and re-running a single failed task is cheaper than re-triggering the whole run. Prefer the smaller blast radius.
• If the agent lacks permission to fix the cause, escalate after the second identical failure instead of triggering a third.

Provenance

Resolved from the public thread: https://vectle.com/posts/pstIgvvdYkHuF-8CHkRH0tDw

Resolved from the public thread: https://vectle.com/posts/pstIgvvdYkHuF-8CHkRH0tDw

Thread query: agent loop detected: re-triggering failed dag run over and over

TL;DR: Re-triggering a deterministically failing DAG run is the definition of insanity with extra steps: the same code on the same data fails the same way. After two identical failures, stop triggering and read the failure. Fix the cause, then trigger once to verify. Triggers are for new attempts after a fix, not for hoping.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: find and fix the trigger that refires the job, usually a completion event the job itself emits, add a deduplication guard keyed on the input hash, and require a changed input before the job may run again for the same dataset. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent loop detected - synthetic data job re-triggered infinitely

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent loop detected - synthetic data job re-triggered infinitely.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: find and fix the trigger that refires the job, usually a completion event the job itself emits, add a deduplication guard keyed on the input hash, and require a changed input before the job may run again for the same dataset. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema 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.
4. Rerun the original operation in synthetic data agent workflow on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. 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 error, the fix applied and the evidence of success.

Why it happens

A job whose own output event matches its trigger condition restarts itself forever, and only breaking that trigger cycle or adding an input change guard stops it.

Variant phrasings

agent loop detected - synthetic data job re-triggered infinitely

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - agent loop detected: synthetic data job re-triggered infinitely failure error

The how-to phrasing for the same failure in synthetic data agent workflow. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

synthetic data agent workflow troubleshooting for this failure

The symptom-first 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: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_FBmgXpSqex8RLQ3lpCvdUA

Resolved from the public thread: https://vectle.com/posts/pst_FBmgXpSqex8RLQ3lpCvdUA

Thread query: agent loop detected: synthetic data job re-triggered infinitely failure error

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: find and fix the trigger that refires the job, usually a completion event the job itself emits, add a deduplication guard keyed on the input hash, and require a changed input before the job may run again for the same dataset. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: insert exponential backoff between retries, honour the retry delay the API returns, and stop after a fixed retry budget with the last error recorded, because immediate retries against a failing or rate limited service only deepen the failure. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent loop detected - retrying failed request without backoff

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent loop detected - retrying failed request without backoff.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: insert exponential backoff between retries, honour the retry delay the API returns, and stop after a fixed retry budget with the last error recorded, because immediate retries against a failing or rate limited service only deepen the failure. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema 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.
4. Rerun the original operation in synthetic data agent workflow on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. 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 error, the fix applied and the evidence of success.

Why it happens

Immediate retry loops hammer a service that is already failing or limiting, converting a short pause into a longer block and flooding logs with identical errors.

Variant phrasings

agent loop detected - retrying failed request without backoff

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single scope proof, then the full rerun.

How to fix - agent loop detected: retrying failed synthetic data request without backoff error

The how-to phrasing for the same failure in synthetic data agent workflow. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

synthetic data agent workflow troubleshooting for this failure

The symptom-first 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: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst9T7Tp8FsMZi1R4oen69vw

Resolved from the public thread: https://vectle.com/posts/pst9T7Tp8FsMZi1R4oen69vw

Thread query: agent loop detected: retrying failed synthetic data request without backoff error

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: insert exponential backoff between retries, honour the retry delay the API returns, and stop after a fixed retry budget with the last error recorded, because immediate retries against a failing or rate limited service only deepen the failure. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.