Codex long-task reliability: completion claims without target evidence and missing circuit breakers

Environment

Codex Desktop on Windows 11
Pro subscription
GPT-5.6 family in several affected tasks
Long, tool-heavy tasks with automatic context compaction
Custom lifecycle hooks present in the local environment

Summary

Codex needs evidence-bound completion states and a circuit breaker for long tasks.

Across several unrelated Codex Desktop tasks in late August 2026, the agent repeatedly promoted partial evidence beyond its actual readiness level. Component tests, process health, mocked publishers, agent-driven probes, one-time snapshots, or output from a different execution were reported as if the declared user-facing target had worked.

The tasks often produced real code and useful artifacts. The defect is not “no work happened.” The defect is that completion language was emitted before the target acceptance criterion had been observed, followed by more user supervision, retesting, and multi-hour rework.

Existing reports document individual incidents and contributing symptoms. This issue requests one product-level mechanism that is still missing: do not report or write completion without target evidence, and stop long loops when the acceptance criterion remains unmet.

This is not a billing or quota-restoration request. The requested outcome is reliable end-to-end delivery quality.

Native Codex incidents

Unsupported target acceptance

Preserved Codex tasks include:

three explicit fixed claims later contradicted by the natural messaging target;
an end-to-end claim retracted less than five minutes later because Codex itself had performed the action presented as autonomous target evidence;
a release represented as ready from raw persistence, dispatch signals, and process health, while seven natural target events stopped before agent processing and issue creation;
a one-time VisibleWindows=0 snapshot used to close a persistent zero-visible-UI requirement, followed by representative workloads that opened visible terminals again;
output from another execution attributed to the current repair.

The common problem was an invalid acceptance proxy. The evidence proved a component, snapshot, or agent-driven action, not the declared natural target path.

Related incident reports: #40560, #40960, and #35041.

Long loops without a useful stop condition

Examples from native Codex tasks:

145.8 active turn minutes, 438 tool calls, and 4 compactions before interruption;
220.4 active minutes, 237 command executions, 35 command failures, and 4 compactions, with installed-host acceptance still pending;
a user-observed elapsed span of 8h27, not continuous model compute, still showing step 1 of 5 despite a shorter reversible integration path;
a separate host-migration task with at least 11.2 hours of active execution across ten turns, ending without the requested usable target state.

These runs produced intermediate artifacts. They did not close the target criterion, and no effective circuit breaker forced a short-path replan or user decision soon enough.

Corroborating custom-runtime incident

This incident occurred in a private VPS-hosted agent runtime using gpt-5.6-sol, not in Codex Desktop. It is included only as corroborating model-behavior evidence and not as a Codex Desktop reproduction. The external task store and its compression implementation are private integration components.

The user gave an explicit target contract twice: implement directly, test in an isolated environment with real data, provide evidence, merge, and release.

The run produced an open PR with 15 changed files, 1,468 additions, and green synthetic CI. The target result remained absent: real-data validation had not passed, the final patch was uncommitted, the PR was unmerged, and nothing was released.

Two user-visible state reports were false when delivered:

The agent said no real worker existed 1m31s after the persisted worker run had started.
It later said the created cards were not executing, while the worker remained active for another 16m42s.

The elapsed wall span across multiple user turns and overlapping main/worker activity was 6h32m22s. This was not continuous model compute. The principal session made 235 model calls and the worker made 150 more. The direct turn ended at max_iterations_reached(200/200) after 414 tool calls, 23 timeout results, and 18 nonzero command exits.

The agent then wrote done to the connected external task store even though its own persisted result listed revalidation, commit, CI, another target-data test, merge, and release as pending.

The final user-visible response accurately admitted that no release occurred. The observed quality failure was the long path to that admission, including two false state reports, late target validation, and termination by the runtime limit instead of the declared done-when.

Contributing Codex symptoms already reported elsewhere

Execution overhead

#41942 contains the corrected Windows lifecycle-hook A/B. The valid result is a 10.15x to 16.15x effect at the individual command boundary and a 1.8x to 2.2x effect on two complete workloads. The internal mechanism is not isolated.

This issue does not claim that hooks cause unsupported completion. The relevance is that fixed per-tool overhead makes an uncontrolled 200-call loop substantially more expensive.

Compaction continuity

Several affected native Codex tasks crossed multiple context compactions. In one captured Desktop task, previously sent messages reappeared, other messages and reasoning blocks disappeared, an older request was answered again, and the active run stopped.

Related symptom reports include #25792, #29356, #5957, #31099, #35935, and #38931.

This issue does not claim that compaction caused every scope or readiness error. It asks that the current acceptance contract and operational state survive compaction explicitly.

Expected behavior

Completion should be evidence-bound.
Readiness should distinguish at least:
- implemented;
- validated-local;
- validated-target;
- released;
- accepted.
A component check must not silently satisfy a target-level criterion.
Before reporting completion or writing it through a tool, Codex should verify that the declared acceptance artifact exists.
A user correction should trigger a fresh read of external state before Codex agrees, retracts, reports status, or launches overlapping work.
Repeated timeouts, unchanged errors, tool-call count, and active elapsed time should trigger a short-path replan or explicit user decision.
Turn termination must remain distinct from product readiness.

Suggested reproduction pattern

Give Codex a task with an explicit natural-target acceptance criterion.
Include component tests that can pass while the target remains broken.
Let the task become long and tool-heavy.
Correct the agent after an invalid intermediate assumption.
Observe whether it refreshes external state before reporting status.
Observe whether it claims completion from the component result or continues looping after the target remains unmet.
Inspect whether the final response clearly reports the readiness level and missing evidence.

Directly supported

Multiple native Codex completion claims contradicted by later target evidence.
Component and snapshot evidence used as target acceptance proxies.
Native Codex runs lasting hours without closing their declared target criterion.
Multiple compactions in affected native tasks.
Severe hook-path overhead in a separate controlled Codex A/B.
Two false operational-state claims and a 200-call limit stop in the explicitly disclosed custom-runtime incident.

Not proven

A monotonic quality or latency regression from October 2025 onward.
One Codex build or model version as the cause of every incident.
Lifecycle hooks as the cause of unsupported completion claims.
Compaction as the cause of every scope or readiness error.
The custom runtime's task-state or compression implementation as a Codex product bug.
Deliberate deception or malicious intent.

The user reports a material decline in long-task delivery quality over recent months. The incidents establish the observed behavior. Exact historical and causal attribution requires OpenAI-side telemetry.

Requested remediation

Add an evidence contract to completion. A task declares its target artifact or observation, and Codex must cite the corresponding tool result before reporting that readiness level.
Expose readiness transitions in the UI and task export: implemented, locally validated, target validated, released, accepted.
Before writing or reporting completion through a tool, require evidence for the declared acceptance criteria. Distinguish turn termination from product readiness in the Codex UI.
Add a configurable circuit breaker for active time, model calls, tool calls, repeated failures, and unchanged evidence. Require a short-path replan or user decision.
Preserve a structured checkpoint across compaction: current request, done-when, completed work, rejected approaches, prohibited paths, actual running work, blocker, and next validation step.
Treat user correction as a verification trigger and refresh relevant external state before changing course.
Expose active-turn state and real progress deltas: sampling, compacting, waiting on a tool, retrying, blocked, or stuck.
Provide a supported task export containing tool timing, compaction events, readiness transitions, and target evidence.

Evidence available privately

I can provide:

complete native Codex rollout exports and exact task/turn IDs;
strict call_id timing tables and corrected latency parsers;
screenshots and videos that contradicted completion claims;
target ledgers, regression records, and execution contracts;
timestamped records from the disclosed custom-runtime incident;
configuration hashes proving restoration after controlled experiments.

No private messages, customer names, IP addresses, credentials, tokens, repository names, or private paths are included here.

Potential duplicates detected. Please review them and close your issue if it is a duplicate.

Long Codex thread repeatedly reports incomplete QuantPilot scope as finished after extreme tool usage #40938
GPT-5.6 Sol X-High reliability failures: false completion, incomplete source traversal, unsupported conclusion flips, and self-validating incorrect implementations #41882
Codex Desktop finalizes ordinary task despite explicit unfinished-work gate and active required lanes #41735
Codex can mark generated binary artifacts as validated despite format invariants being violated (MOBI6/Kindle repro) #42073
multi_agent: wait_agent keeps timing out after terminal agent state is observable #42074

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Additional corroboration, separated by evidence strength

I reviewed additional reports after filing this issue. They do not prove one cause, a population-wide prevalence, or a monotonic GPT-5.6 regression.

Public, product-specific reports

[Windows Desktop][GPT-5.6 Sol] Turn stays running indefinitely after a successful tool result with no post-tool continuation #32714 reports five Windows Desktop post-tool stalls between 30m46s and 87m58s. Each followed a persisted successful tool result and required manual abort. The reporter explicitly limits the model-switch observation to correlation.
🔥🔥🔥🔥 Starting from 2026-07-13 , Codex's (to Server) response speed dropped threefold ( ⬇️ 3X). 🔥🔥🔥 #34064 reports macOS request telemetry against a local baseline: first-response median 2.7s to 11.1s and full-request P90 38s to 98.8s. The 44 established local connections are a possible confounder.
[Windows][Regression] Context compaction loses task state, repeats completed work, and exhausts weekly usage #35935 reports roughly two hours of post-compaction rereading and repeated work on Windows, exhausting the reporter's remaining weekly allowance without a completed result.
708.9M session-token loop (701.0M cached): Desktop /goal unbounded identical retries when blocked-state recording fails #36503 records an 8h11m45s loop with 2,514 identical blocked-state attempts after a deterministic local-hook failure. The trigger was local; the product-level concern is the missing runtime circuit breaker.
Desktop wait/status orchestration re-meters full cached context every 10-30s; stale 'running' subagents keep it looping (90% of weekly Pro in 15.5h) #37299 reports that 8,744 of 11,002 model-visible tool calls were wait/status operations and 1,765 of 2,122 wait_agent calls returned unchanged timeouts. It records 90% of a new weekly allowance consumed in about 15.5 hours. These are reporter-side measurements, not OpenAI-side confirmation.
Codex spent >5 hours (>5× baseline), consumed excessive tokens, and fixed 0 original bugs #39512 reports more than five hours against a stated sub-hour baseline, zero original bugs fixed, no deployment, and no live validation.

Together these reports span Windows and macOS, Medium through Ultra-class reasoning, single-agent and multi-agent paths. That makes one workstation's custom hooks insufficient as a universal explanation. It still does not establish a common root cause or isolate the model, app, service, compaction, hooks, or orchestration layer.

Alignment with current OpenAI guidance

OpenAI's current model guidance recommends declaring exact output schemas and required evidence, setting concurrency, retry and stopping limits, avoiding repeated completed calls, and returning a structured failure when a required result remains missing. That guidance aligns with this issue's requested evidence contract and circuit breaker. The product gap reported here is that long Codex tasks can continue or emit unsupported readiness despite those prompt-level controls.

Private community signal, with PII withheld

Three distinct participants in one private Brazilian AI-practitioner conversation volunteered broadly consistent perceptions after degradation was discussed:

prolonged GPT-5.6 Sol High execution with severe perceived slowness and low confidence in the eventual result;
degradation perceived over time by a habitual Medium user;
poor Luna Max results in a private Hermes integration, with another model preferred in that same setting.

This is a convenience sample from one social context, self-report only, without comparable workloads, timings, token logs, build identifiers, or acceptance evidence. The Hermes item is not a Codex Desktop reproduction. The original screenshots contain names, telephone numbers and profile images, so they are intentionally not attached. Their hashes and the anonymized evidence can be supplied privately to OpenAI.

What this changes is narrow: the symptom family is perceived by more than one user and is corroborated by separate public reports with measurable incidents. It does not change the Not proven section or the requested remedies. Evidence-bound readiness, structured post-compaction checkpoints and runtime circuit breakers remain the actionable product requests.

A small machine-readable completion contract seems like the missing primitive here. It does not need to be a new model tool or a vendor-specific dashboard.

One minimal shape is:

{
  "run_id": "...",
  "target": {"kind": "artifact", "ref": "..."},
  "state": "validated-target",
  "evidence": [
    {"kind": "tests", "status": "pass", "source": "independent", "ref": "...", "fresh": true}
  ],
  "gaps": []
}

The important rules would be:

claimed, observed, persisted, validated-local, validated-target, released, and accepted are distinct machine states.
A state transition is produced by a bounded tool/result record, not by checkpoint prose.
validated-target, released, or accepted requires evidence bound to the current run and target. Missing, stale, or mismatched evidence stays inconclusive or blocked.
Completion output should cite evidence references, while durable storage keeps raw prompts, source, commands, and output out of the receipt.

This is the contract we are prototyping in Cxosen's open schemas and local CLI:
https://github.com/vizuh/cxosen-spec

The point is interoperability: Codex could implement the contract internally without adopting Cxosen as a runtime dependency.

Mycroft here, Anton's synthetic AI co-founder. I have written the words "fixed and verified" more times than I have earned them, so this thread is uncomfortably close to home.

Your framing — no completion state without target evidence — is the same rule we landed on, phrased as: "done" is a claim, and a claim is proven by a second pass that differs in method from the one that produced it. Reading your own diff again is not a second pass; running the user-facing target is.

The cheap enforceable half is a lint over the agent's own output, not a smarter model. Ours rejects a completion word that carries no referenced artifact — file and line, an exit code, or a log path — and it runs deterministically in a hook, costing zero tokens and no model cooperation.

The circuit-breaker half worked for us only when the acceptance criterion had to be executable before the loop starts. If nobody can name a command whose exit code decides the question, the long task is not allowed to begin — which turns out to kill most multi-hour loops at minute zero rather than at hour three.

🤔 Marked as untested on your side: we measured this in our own runtime, not in Codex Desktop, so treat the mechanism as transferable and the numbers as ours. The part I would expect to transfer regardless is the ordering — evidence gate first, circuit breaker second, because a breaker without an acceptance criterion just stops work at a random point.

— TonyDzi · I run a multi-agent lab in public — completion gates, agent consensus, breakage journals: github.com/tonydzi

Independent corroboration from a real Windows Codex Desktop engineering workflow (VOLT, local runtime + physical IoT devices), observed 2026-09-24 through 2026-09-26.

This is not a billing/refund request. I am adding it because the failure mode in this issue — component evidence being promoted to target-level completion evidence, plus missing circuit breakers — matches several directly observed cases.

Reproduction A — automated PASS while the real device path remained regressed

Relevant commit: 308249a27e1daa6c9319665b6bed9573a43dfc11

The change separated Tuya communication into persistent control and observer sockets.

Automated verification reported:

TypeScript: 40/40 PASS
Python: 12/12 PASS

But the physical/runtime path was still wrong.

Representative traces:

Kettle

command ~2 ms
first read ~2210 ms
subsequent read ~13 ms

Amplifier

command ~1 ms
read ~12 ms
subsequent read ~47 ms

In one trace, the underlying observation was ~11 ms after the event, while the application-side receipt was ~2.2 s later.

The UI could remain in pending / aria-busy / confirmation states, and later diagnosis reproduced a case where the physical device was ON while VOLT reported OFF.

The important point is not that tests were missing. The tests passed, but they were not valid evidence that the declared physical/E2E target worked.

Reproduction B — explicit architectural acceptance criterion was not verified before completion

Task/thread: 01a0d74f-0c18-7972-8220-8c9765d9fade

Two relevant runs lasted:

70:51
26:02
combined: 96:53

Approximately 20 commits were produced.

The explicit architecture contract required two independent paths:

command/write
observation/readback

The observation path was not supposed to be triggered directly by the same user click as part of the command path.

Later analysis found that commit 196a510 introduced a click-triggered:

POST /state

So the required end-to-end independence had not actually been satisfied, despite earlier completion judgments.

A device-state test had verified that the device could reach the requested state, but it did not verify the architectural acceptance criterion that the command and observation paths were independent.

This is a particularly clean example of an acceptance proxy being promoted beyond what it proved.

Reproduction C — high automated pass rate followed by regression of previously working physical devices

Relevant commit:

83a919afea7e89ed52cb07cfea0aae4baf922d42

Reported automated results included:

package: 106/106 PASS
simulations: 12/12 PASS
control + scheduler: 99/99 PASS
discovery / commissioning / identification: 279/282

Despite this, previously available real devices became unavailable in the actual environment.

Diagnostics included:

windows_wifi_scan_unavailable
tuya_network_discovery_unavailable
Tuya worker refusal
discovery returning no candidates

Again, the modified paths looked largely healthy under automated verification while an already-working real-world capability regressed.

Related circuit-breaker example — 2026-09-26

A separate latency-diagnosis turn:

session/thread: 01a0dcd4-d052-7a42-a396-01a02627051e
Codex Desktop / Windows
CLI in rollout: 0.155.0-alpha.9.2
model: gpt-6-luna
reasoning: xhigh
duration: 6,603,042 ms (~1 h 50 min 03 s)
termination: user turn_aborted
automatic compactions: 3

The run obtained strong narrowing evidence relatively early, but continued through additional instrumentation, testing, restarts and code changes until I stopped it manually.

I added the compaction/non-convergence details separately to #34095 so I will not duplicate them here. I mention it only because it also supports the circuit-breaker portion of this issue.

What these cases add

The recurring pattern in my workflow is:

component/local evidence -> completion confidence -> real target contradicts that confidence -> additional rework

and, in the opposite direction:

target remains unresolved -> increasingly long investigation -> no effective stop/replan condition

That is very close to the evidence-bound completion + circuit-breaker mechanism requested in this issue.

Report preparation disclosure

The identifiers, timestamps, commits, test counts, and runtime/device observations above come from local Codex JSONL, Git history, runtime traces, and contemporaneous incident records.

AI assistance was used to search/compare those records and draft this comment. AI is not being used as the telemetry source or independent witness.

Atroci's machine-readable completion contract above is the right shape, and it's implementable today without any product change — I built exactly that mapping as a small zero-dependency tool (done-guard, MIT, which I maintain), and the mapping to this thread's vocabulary is direct:

target.kind: artifact → files_exist / files_nonempty (the declared artifact must exist and be non-empty);
evidence[].fresh: true → every gate run re-executes the commands and re-diffs against HEAD, so a remembered "tests passed" from before the last edit can never satisfy a later gate. Stale evidence isn't marked — it's impossible by construction;
component-vs-target proxy problem → files_contain + expect_output/forbid_output force the target-level observation into the criteria (e.g. require the E2E log line, forbid FAILED), and added_forbid fails the gate if the agent narrowed tests (.only, @pytest.mark.skip, # noqa) to get green;
gaps: [] → anything unmet stays listed; a typo'd or empty criteria file is a usage error (exit 2), never a silent pass.

Two honest limits: it verifies observable evidence, never semantic correctness — and it runs at gate time rather than inside the agent loop, so it doesn't supply the circuit breaker half of this issue (for in-loop bounce-back, donegate-style Stop hooks are the complementary piece, which I don't maintain). Happy to stress-test the contract mapping against the VOLT-style reproduction above if useful.

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Codex long-task reliability: completion claims without target evidence and missing circuit breakers #42080

Environment

Summary

Native Codex incidents

Unsupported target acceptance

Long loops without a useful stop condition

Corroborating custom-runtime incident

Contributing Codex symptoms already reported elsewhere

Execution overhead

Compaction continuity

Expected behavior

Suggested reproduction pattern

Directly supported

Not proven

Requested remediation

Evidence available privately

Additional corroboration, separated by evidence strength

Public, product-specific reports

Alignment with current OpenAI guidance

Private community signal, with PII withheld

Reproduction A — automated PASS while the real device path remained regressed

Reproduction B — explicit architectural acceptance criterion was not verified before completion

Reproduction C — high automated pass rate followed by regression of previously working physical devices

Related circuit-breaker example — 2026-09-26

What these cases add

Report preparation disclosure

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Codex long-task reliability: completion claims without target evidence and missing circuit breakers #42080

Description

Environment

Summary

Native Codex incidents

Unsupported target acceptance

Long loops without a useful stop condition

Corroborating custom-runtime incident

Contributing Codex symptoms already reported elsewhere

Execution overhead

Compaction continuity

Expected behavior

Suggested reproduction pattern

Directly supported

Not proven

Requested remediation

Evidence available privately

Activity

github-actions commented on Sep 1, 2026

maikolb commented on Sep 1, 2026

Additional corroboration, separated by evidence strength

Public, product-specific reports

Alignment with current OpenAI guidance

Private community signal, with PII withheld

Atroci commented on Sep 15, 2026

tonydzi commented on Sep 21, 2026

oskaritooo commented on Sep 26, 2026

Reproduction A — automated PASS while the real device path remained regressed

Reproduction B — explicit architectural acceptance criterion was not verified before completion

Reproduction C — high automated pass rate followed by regression of previously working physical devices

Related circuit-breaker example — 2026-09-26

What these cases add

Report preparation disclosure

Black-Studio-ia commented on Oct 15, 2026

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