Start by classifying the failure before changing the prompt or pressing retry. Read the structured error code, check whether the session and sandbox are actually connected, inspect the individual tool result, and verify side effects before replaying anything. A sandbox timeout can mean an invalid request, exhausted context or session budget, failed environment provisioning, a disconnected self-hosted executor, an idle session, or a command that failed inside an otherwise successful turn. The correct fix depends on that layer.
A fast diagnostic sequence
Use this order whenever an agent reports a sandbox error, hangs while starting, or appears to finish without completing a tool action. It keeps a transient connection problem separate from bad input and prevents duplicate work.
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- Read the machine-readable error. Record the structured code and its message. The code identifies the failure class; the message supplies the immediate detail. Do not treat every timeout as the same problem.
- Retrieve the session and turn. Establish whether the session is active, completed, waiting for an action, or failed. A failed turn does not necessarily mean the session is unusable.
- Check environment state. For a hosted environment, wait for
connectedbefore attempting live file operations. If it isprovisioning, setup is still running. If it isfailed, inspect the environment error or failure event. - Inspect the tool result. A turn can finish after a tool has failed or after a mid-turn disconnect. The final response alone is not proof that a command ran successfully.
- Check for side effects before retrying. Retrieve the prior turn, saved items, changed files, and any external calls you can audit. Then decide whether the next attempt should continue, compensate, or start over.
- Bound retries. For transient overload, rate limits, timeouts, or temporary service failures, honor
Retry-After, set a maximum attempt count or deadline, and stop if the error category changes.
This sequence is an operational way to apply the documented OpenAI Agents API error and lifecycle guidance. The exact codes are OpenAI terminology; other agent frameworks may expose different names.
Identify which layer failed
OpenAI’s error guide separates request validation, size and budget limits, environment connectivity, command execution, and provider faults. Classifying the layer first tells you what evidence to collect and what not to retry.
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| Error or symptom | What it usually means | First action |
|---|---|---|
invalid_request |
The request, parameter, credential, or tool schema is not acceptable. | Correct the request or credentials. Retrying unchanged input will not help. |
context_length_exceeded |
Input, conversation history, tool definitions, or output requirements exceed the model’s context capacity. | Reduce the payload, remove unnecessary tool schemas, or continue in a new session with a concise summary. |
session_budget_exceeded |
The session has consumed its permitted usage budget. | Start a new session and carry forward only the information needed to continue. |
sandbox_error |
A sandbox-side operation failed; the message and environment event identify the narrower cause. | Inspect environment state, setup logs, and the individual tool result. |
executor_version_incompatible |
The executor version cannot work with the requested session or API capability. | Install or launch a compatible executor version before creating another session. |
environment_connection_failed |
The executor or hosted environment could not establish its connection. | Check startup, network policy, connection events, and logs. |
environment_connection_timeout |
Connection setup did not complete within the provider’s waiting period. | Investigate executor reachability and outbound access; verify the original request before resubmitting. |
idle_timeout |
The environment was inactive long enough for the session to expire. | Create a new session and provide its inputs again. |
internal_error |
A temporary provider-side failure or an unclassified server problem occurred. | Check provider health, preserve the failed request for correlation, and retry only within a bounded policy. |
The table describes the documented OpenAI API categories, not a universal taxonomy. If your framework uses different codes, apply the same principle: use its structured category rather than inferring a cause from the word “timeout.”
Check the session and sandbox state before touching files
Hosted environments
A hosted environment has a lifecycle independent of an individual model turn. provisioning means packages, files, and setup commands are still being prepared. connected means the environment is live and file operations can proceed. failed means the environment has a recorded error that should be fixed before another session is created.
- Retrieve the session and the turn that reported the failure.
- Read the environment status and the associated failure event, not just the assistant’s prose.
- Do not issue a compensating file edit while the status is still
provisioning; the command may race setup and produce a misleading second failure. - If the status is
failed, preserve the error details, correct the setup cause, and then create a replacement session with the required inputs.
Why a failed turn can be recoverable
A turn is one interaction, while the session and environment can outlive it. A malformed tool call may fail one turn while leaving the session active. Conversely, a turn marked complete may contain a failed tool result. Always inspect both levels before deciding that the entire run is lost.
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Fix hosted-environment provisioning failures
When a hosted sandbox never reaches connected, inspect the setup inputs rather than repeatedly sending the same agent instruction.
Packages and setup commands
Verify package names, versions, installation order, and exit status. A setup command that cannot resolve a package, waits for interactive input, or exits nonzero can prevent the environment from becoming usable. Remove unnecessary installation work from the startup path and make commands non-interactive where the platform requires it.
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Attached files and paths
Confirm that every declared input file exists, that its path matches the path used by the agent, and that the session includes the intended attachment. A missing or unreadable input can look like a tool failure later, while a wrong working directory can make a successful command appear to have produced no output.
Network policy and redirects
If setup or a tool needs the network, inspect the policy and the final destination after redirects. A request may be allowed to its first host but blocked when that host redirects to another domain. Permit only the destinations the workflow actually needs, and verify each redirected host against the policy instead of enabling broad egress.
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Read the failure event
The hosted-environment troubleshooting guidance directs operators to the environment failure event. It can distinguish an installation error from a blocked request or an unavailable dependency. Use that event as the primary evidence; a generic “sandbox error” message is only a category.
Diagnose a self-hosted executor that will not connect
Self-hosting moves execution to compute you control, but it also makes executor startup, network access, logging, and persistence your responsibility. It is not an automatic cure for timeouts.
- Confirm the process is running. Start the executor with the session’s environment ID and the configured remote URL. Check that it has not exited during initialization.
- Check outbound access. The documented setup requires access to https://api.openai.com and
wss://codex-cloud-environments.chatgpt.com. Firewalls, proxies, DNS, TLS inspection, and allowlists must permit the connection path used by your deployment. - Follow connection events.
pendingmeans the service is waiting for the executor;connectedmeans it is ready;failedmeans inspect the environment error and executor logs. - Compare identifiers. Ensure the executor is using the same environment ID and session context that the API request expects. A healthy executor attached to a different ID will not satisfy the waiting session.
- Check provider health as well as local logs. A local process can be healthy while the control-plane connection is degraded. Correlate the event timestamp with the provider’s status information.
Do not assume that switching from hosted to self-hosted removes the root cause. It changes who provisions compute and controls egress; the operator now has to keep the executor available, maintain compatible versions, provide network access, and design storage that survives replacement.
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When a tool fails but the turn completes
Inspect the tool result and the final response separately. A mid-turn disconnect can kill a command while allowing the turn to close normally. The command is not automatically restarted, and the platform does not silently reconnect and replay it.
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- Check whether the disconnect happened before execution, during execution, or while the result was being returned.
- Do not infer success from a natural-language sentence such as “the task is complete.” Require an observable artifact or a successful tool result.
- If the command could have partially changed state, inspect that state before issuing a replacement command.
OpenAI’s recovery guidance states: “Inspect tool results even when a turn completes.” That instruction matters most for commands that modify files, publish data, send messages, or call an external service.
Retry without duplicating side effects
Determine whether the first attempt ran
Before replaying a timed-out operation, retrieve the original session and turn, inspect saved items, and examine the target system. A timeout can occur after the sandbox completed the action but before the result reached the agent. Repeating a non-idempotent operation can create duplicate records, send a second notification, or overwrite a newer file.
Use an idempotent recovery design
- Give each external operation a unique request or job identifier that the destination can de-duplicate.
- Write outputs to a temporary path and rename atomically only after validation.
- Record a completion marker containing the input identifier and result location.
- For destructive operations, require a fresh state check or explicit confirmation after a timeout.
- Separate “did the command start?” from “did the command finish?” in your audit record.
Bound transient retries
For overload, rate limits, temporary service failures, and connection timeouts, honor the server’s Retry-After value when present. Set both an attempt limit and an overall deadline. Stop automatic retries when the error changes to invalid input, authentication, billing, a budget limit, or a failed environment; those require a correction rather than persistence.
When to create a new session
If the session is failed, fix the underlying cause and create a new session with the necessary inputs. If only the context or session budget is exhausted, carry forward a short, verified summary instead of copying the entire history. If an environment is replaced, do not assume its old files are still present merely because you reused the same environment ID.
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Understand the provider’s timeout and storage lifecycle
The five-minute input-connection wait
For an input-time environment connection, the OpenAI API waits up to five minutes. If the connection has not arrived when that period expires, submission fails. A connection that arrives later does not replay the timed-out input, and a process crash does not guarantee recovery of pending input. Before resubmitting, inspect the original request and session so you know whether the input was accepted or may still have produced side effects.
The one-hour hosted inactivity limit
OpenAI’s hosted-sandbox documentation says that a sandbox can be deleted after one hour with no activity and no keep-alives. That limit is provider-specific and not configurable. Treat a long pause as a lifecycle event: save required outputs outside the ephemeral environment and be prepared to create a new session with its inputs.
Replacement compute and persistent files
Reusing an environment ID does not restore files in replacement compute. If files must survive a host replacement or a new session, store them in the provider’s supported persistent storage or in snapshots under your control. Verify the saved artifact before retrying the agent.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Hosted versus self-hosted sandbox execution
| Decision area | Hosted sandbox | Self-hosted executor |
|---|---|---|
| Compute provisioning | The provider provisions and manages the Linux workspace. | Your infrastructure provisions and runs the executor. |
| Connection responsibility | You monitor environment states and provider events. | You also maintain the executor process, compatible version, remote URL, and outbound connectivity. |
| Network egress | Controlled by the hosted environment’s policy and approved destinations. | Controlled by your firewall, proxy, DNS, and network policy, while the control-plane connection still has to work. |
| File lifetime | Subject to the hosted lifecycle, including deletion after prolonged inactivity; persist important artifacts separately. | Determined by your compute and storage design; replacement machines do not automatically contain old files. |
| Telemetry | Environment status and failure events expose provisioning and connection state. | You can inspect those events plus executor logs and host-level metrics. |
| Operational trade-off | Less infrastructure to operate, but less control over provisioning and lifecycle. | More control over compute, network, and storage, with more responsibility for availability and compatibility. |
Anthropic’s deployment documentation makes a similar hosted-versus-customer-controlled distinction and notes that tool inputs and outputs still pass through its control plane. The general lesson is provider-specific: self-hosting changes the boundary of responsibility; it does not make network, provisioning, or persistence problems disappear.
Protect credentials and network access while troubleshooting
Debugging often tempts teams to grant broad permissions. That can turn a timeout into a security incident. OpenAI’s Sandbox security documentation states: “Agent-generated code can access the files, credentials, and network available to its environment.” Treat every permission added during diagnosis as a production decision.
Best Value
- Use least-privilege egress. Allow only the approved destinations required by the task. Check redirect targets rather than allowing an entire category of domains.
- Keep application keys out of the sandbox. Broker third-party access through a proxy or vault pattern that can issue narrowly scoped, short-lived credentials and revoke them independently.
- Distinguish connection locations. An executor-initiated MCP connection in your environment is different from a remote MCP call initiated by the provider. Apply policy to the component that actually opens the connection.
- Separate diagnostic credentials. Use test accounts and restricted tokens while reproducing a failure. Never paste a production secret into a prompt, log, or tool argument.
- Capture enough logs, not everything. Redact tokens, cookies, personal data, and file contents before sharing executor logs or failure events.
A blocked request should be fixed by reviewing the intended destination and policy, not by opening unrestricted outbound access.
Local SDK development is not automatically isolated
The OpenAI Agents SDK guide describes the Linux UnixLocalSandboxClient as running commands as host processes without adding operating-system-level confinement. On macOS, filesystem restrictions do not provide network isolation. That path can be useful for trusted local development, but it is not an appropriate boundary for untrusted commands.
For untrusted code, use a correctly configured Docker or hosted sandbox, or another external isolation mechanism that enforces filesystem, process, and network boundaries. If a local test times out, first establish whether the issue is in the SDK client, the host process, or the remote control plane; do not interpret local execution behavior as proof about hosted sandbox reliability.
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| Symptom or evidence | Inspect first | Supported response |
|---|---|---|
environment_connection_failed or environment_connection_timeout |
Executor startup, outbound connection setup, network access, and executor logs. | Correct startup or network configuration, then verify connection events before resubmitting. |
Hosted environment remains provisioning |
Whether setup is still active and whether the provider has emitted a failure event. | Wait for connected; do not start live file operations prematurely. |
Hosted environment is failed |
Environment failure event, packages, input files, and setup commands. | Fix the setup issue before creating another session. |
| A sandbox request is blocked | Network policy and the destination reached after redirects. | Permit only intended, approved destinations and test the complete redirect chain. |
| A tool failed but the turn completed | Tool result, final response, and evidence of a mid-turn disconnect. | Treat the tool failure as real; verify state before rerunning the command. |
idle_timeout |
Hosted-environment inactivity and keep-alive history. | Create a new session and supply inputs again. |
| Context, size, or session-budget error | Input size, conversation history, tool schemas, and usage budget. | Trim the request or start a new session with a concise summary. |
| A retry appears necessary | Prior turn status, saved items, side effects, and Retry-After. |
Check first, then use a bounded retry policy and stop when the error changes. |
A practical incident record
For recurring failures, keep a small record for each incident. Capture the provider and SDK version, session and turn identifiers, exact structured code, environment state transitions, executor version, timestamps in UTC, network destinations, setup command results, tool results, and whether any external side effect was observed. This makes a second attempt safer and lets an operator distinguish a reproducible configuration defect from a temporary provider outage.
When escalating, include the minimal reproducible request and redacted logs. State whether the environment was hosted or self-hosted, whether the executor ever reached connected, and whether the original input may still have been processed. Those details are more useful than a screenshot that only says “timed out.”
Quick Recap
What to remember
- Classify the structured error before changing prompts or retrying.
- Wait for a hosted environment to become
connected, and read the failure event when it becomesfailed. - For self-hosted execution, verify the executor, environment ID, outbound access, connection events, and logs.
- Inspect individual tool results even when the overall turn reports completion.
- Check files and external systems before replaying an operation; use idempotency keys and bounded retries.
- Remember that a five-minute input-connection wait, a one-hour hosted inactivity deletion, and environment-file persistence are provider-specific lifecycle rules.
- Keep credentials and network permissions narrowly scoped while you diagnose the failure.
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