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Do not start by rewriting the prompt or blindly retrying. First classify the failure, then verify the session and sandbox state, inspect the individual tool result, and check for side effects before replaying anything. OpenAI’s Agents API uses distinct codes for bad input, exhausted budgets, environment connection problems, command failures and service errors; the right recovery depends on that code.
What a sandbox failure actually tells you
An agent turn can fail at several independent layers. A request may be invalid before execution starts, a session may have exhausted its budget, the environment may still be provisioning, an executor may be unable to connect, or a command may have failed after the agent successfully started work. Treating all of these as “the model timed out” leads to unsafe retries and wasted debugging.
The error code is the machine-readable category. The message adds context such as the affected environment, command or limit. The names below are OpenAI Agents API terminology; other agent frameworks use different labels.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problems| Evidence | Likely layer | Inspect first | Supported response |
|---|---|---|---|
invalid_request, context_length_exceeded |
Request or input | Payload shape, prompt size, tool definitions and schema | Correct or reduce the request; do not retry unchanged input |
session_budget_exceeded |
Session usage | Accumulated tokens, tool calls and session limits | Start a new session with a compact summary and only the required inputs |
sandbox_error, executor_version_incompatible |
Sandbox or executor | Environment error details, image or executor version | Fix the environment or compatibility issue before creating another run |
environment_connection_failed, environment_connection_timeout |
Environment connectivity | Executor startup, outbound access, connection events and logs | Repair provisioning or network connectivity, then reconnect or create a new session as directed |
idle_timeout |
Inactive hosted environment | Last activity and keep-alive behavior | Create a new session and provide its inputs again |
| Tool error with a completed turn | Command or tool execution | Tool result, stderr, exit status and final response | Treat the tool operation as failed unless its result proves success |
internal_error |
Provider service | Provider status, request ID and retry guidance | Use a bounded retry policy; escalate or stop when the error changes |
Size-related errors deserve their own check. A large prompt, transcript, tool definition or schema can exceed a context limit before any sandbox process starts. A session budget error is different: the request may be valid, but the session has consumed its allowed usage through earlier turns and tool calls. In the first case, reduce the payload; in the second, continue in a new session with a short, verified handoff.
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A disciplined diagnostic sequence
Run these checks in order. Save the original request, session identifier and turn identifier before making changes so you can determine whether a later attempt duplicated work.
- Read the structured error. Record the exact code and message, not just the HTTP status or a user-interface banner. A timeout caused by an input-time connection is different from
idle_timeout, and both differ from a command that exceeded its own deadline. Preserve the request and response metadata for correlation with executor or provider logs. - Retrieve the session and turn. A failed turn does not necessarily mean the session is unusable. Check whether the session is active, completed, waiting for an action or failed. Inspect the turn’s events and any saved items. If the session is still active, avoid creating a second session until you know what the first one did.
- Verify environment readiness. For a hosted environment, wait while the status is
provisioning. Live file operations should begin only when the status isconnected. Afailedstatus should lead you to the environment failure event and its error details, not to repeated file commands. - Check setup inputs when provisioning failed. Review package installation, setup commands, attached files, working paths and environment variables. If a request was blocked, examine the destination reached after redirects as well as the original hostname. A policy that permits the first URL but blocks the redirected host can look like a generic connection failure.
- For self-hosted execution, verify the executor path. Confirm that the executor process is running with the session’s environment ID and the configured remote URL. Confirm outbound access to
https://api.openai.comandwss://codex-cloud-environments.chatgpt.comfor the documented OpenAI self-hosted setup. Use connection events:pendingmeans the service is waiting for the executor,connectedmeans it is ready, andfailedmeans you should inspect the environment error and executor logs. - Inspect each tool result. Read the command output, exit code, stderr and any returned file or artifact. A mid-turn disconnect can fail a tool even when the turn receives a final response. A disconnect does not restart a killed command or automatically request reconnection.
- Recover only after checking side effects. Retrieve saved items and inspect files, database records, queues or external API logs touched by the original attempt. Decide whether the operation is idempotent. Retry only transient failures, honor
Retry-After, and impose a maximum attempt count or deadline. Stop automatic retries when the code changes or the limit is reached.
For every check, preserve timestamps. Matching the API event time, executor log time and command start time often reveals whether the failure occurred before process launch, during connection establishment or after work began. Also record the environment ID and executor version; otherwise a replacement process can appear to be the original one.
Hosted sandbox troubleshooting
Wait for the correct state
A hosted workspace is managed compute, so provisioning is part of the request lifecycle. provisioning means setup is still underway; it is not permission to start live file operations. connected is the usable state. When the environment is failed, open the failure event and correct the reported package, file, command or network issue before starting another session.
Check packages, files and setup commands
Failures commonly come from an installation command that cannot resolve a package, an input file that was not attached at the expected path, or a setup script that assumes a missing directory or variable. Make setup deterministic: use explicit paths, fail fast on installation errors, and log the command that produced the failure. Keep setup separate from the agent’s task so you can distinguish an environment problem from an application command problem.
If setup reaches a URL that redirects, check every host in the chain. Network policy is applied to the destination actually contacted, not merely the URL typed into the setup script. Permit only approved destinations, and do not broaden egress until you know which package mirror, artifact host or service is required.
Understand the hosted inactivity limit
OpenAI’s hosted-sandbox documentation says an environment can be deleted after one hour without activity or keep-alives, and that timeout is not configurable. This is a provider-specific lifecycle limit, not a general definition of an agent timeout. Preserve required files in provider storage or snapshots if the workspace must survive replacement or deletion.
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Self-hosted sandbox troubleshooting
What you control
Self-hosting moves the executor into your compute. You control the process, operating system, network route, provisioning and local logs, but you also become responsible for keeping the executor alive, allowing required outbound traffic, updating compatible versions and preserving data.
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Start with the executor’s startup log and verify that it uses the same environment ID associated with the session. Then check the remote URL, DNS resolution, TLS inspection, firewall rules and proxy behavior. Match timestamps from executor logs with API connection events. A long period in pending usually means the provider is waiting for the executor; a transition to failed requires the environment error and local logs rather than another prompt.
Check host health as well as application logs. Exhausted disk space, memory pressure, a stopped container or an expired certificate can prevent the executor from completing its handshake. Provider health information is another useful comparison point: an otherwise healthy executor cannot overcome a provider-side outage.
Do not assume self-hosting eliminates timeouts
Self-hosting can expose the cause of a failure more clearly, but it adds failure modes: a stopped process, blocked egress, incompatible executor version, exhausted host resources or lost local storage. It changes who operates the compute; it does not make network, lifecycle or persistence problems disappear.
Why a turn can complete even though a tool failed
An agent turn is an orchestration record, not a guarantee that every action succeeded. A connection can drop after a command is sent, leaving the command killed while the model still produces a final message. OpenAI’s recovery guidance explicitly says: “Inspect tool results even when a turn completes.”
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Use the tool result as the source of truth for the operation. For a file edit, read the resulting file or compare a checksum. For an external API call, query the provider for the request status. For a job submission, check the job identifier. If there is no verifiable success signal, mark the operation unknown and use an idempotency key or reconciliation step before attempting it again.
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Retry safely and avoid duplicate side effects
Before retrying
- Retrieve the original session and turn rather than relying on a client-side timeout.
- Inspect saved artifacts, modified files, queues, tickets, payments or other external effects.
- Determine whether the command is read-only, idempotent, or inherently non-repeatable.
- Capture the provider’s request ID and any
Retry-Aftervalue.
When a retry is appropriate
Bound retries by both count and time. Honor the server’s Retry-After delay for rate limits and overload. Retry transient connection or internal errors only while the error category remains transient. A changed error, an exhausted budget, invalid credentials, a billing limit or invalid input requires a fix, not more attempts.
When to create a new session
If the session is failed, correct the underlying cause and create a new session with the necessary inputs. If the context or session budget is exhausted, carry forward a short, verified summary instead of the entire transcript. For idle_timeout, the documented recovery is a new session with the inputs supplied again.
Connection timeouts and lost input
For an input-time environment connection, OpenAI’s lifecycle documentation says the API waits up to five minutes. If the connection does not arrive within that window, the 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.
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Before resubmitting, check the original request and session. Confirm whether the input was accepted, rejected or left pending. Reusing an environment ID also does not restore files in replacement compute. Put durable inputs in provider storage or snapshots and treat the environment itself as replaceable.
Hosted versus self-hosted execution
Both models can run agent tools, but the troubleshooting boundary is different. A hosted service provisions and operates the workspace; a self-hosted service gives you control of the executor and its surrounding infrastructure.
| Dimension | Hosted sandbox | Self-hosted sandbox |
|---|---|---|
| Compute provisioning | Provider provisions the managed Linux workspace; inspect hosted environment states and failure events. | Your infrastructure starts and maintains the executor; inspect process, host and orchestrator logs. |
| Network egress | Governed by the provider’s environment policy and approved destinations. | Governed by your firewall, proxy, DNS, routing and provider connection requirements. |
| Connection telemetry | Environment status and lifecycle events expose provisioning, connection and failure states. | Provider events must be correlated with executor logs and local health checks. |
| Persistence | Use provider storage or snapshots; an environment may be deleted after its inactivity limit. | You choose disks and backups, but replacement hosts do not recover unpersisted files. |
| Operational burden | Less executor management, with provider-specific limits and policies. | More control and observability, with responsibility for versions, uptime, networking and storage. |
Other providers make a similar managed-versus-customer-controlled distinction. For example, Anthropic documentation separates cloud-managed sandboxes from self-hosted deployments while noting that tool inputs and outputs still pass through its control plane. Do not assume that a deployment boundary changes where sensitive tool data is transmitted.
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Network and credential security while fixing failures
OpenAI’s Sandbox security documentation warns: “Agent-generated code can access the files, credentials, and network available to its environment.” Troubleshooting should therefore preserve least privilege rather than opening unrestricted egress to make a request pass.
- Allow only the outbound destinations the task requires, and check redirect targets against the same policy.
- Keep application API keys outside the sandbox whenever possible.
- Broker third-party credentials through an external proxy or vault pattern with narrow, auditable permissions.
- Distinguish connections initiated by executor MCPs in your environment from remote MCP calls initiated by the provider.
- Record which command accessed which host so a successful retry does not hide an unintended data path.
A blocked request is not evidence that broad network access is safe. Identify the exact destination and connection owner, then permit the smallest rule that solves the task.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Local SDK development is not automatically confined
The OpenAI Agents SDK guide documents an important limitation: on Linux, UnixLocalSandboxClient runs commands as host processes without adding OS-level confinement. On macOS, filesystem restrictions do not provide network isolation. This path is suitable only when the commands are trusted and the host policy is acceptable.
For untrusted commands, use a properly configured Docker or hosted sandbox, or another external isolation boundary. If a local command fails, debug it as a host-process failure first; do not infer that sandbox-level containment or network policy protected the machine.
A compact decision checklist
- Did you record the exact structured error code and message?
- Is the session active, completed, waiting, or failed?
- Is a hosted environment still
provisioning, alreadyconnected, orfailed? - For self-hosting, is the executor running with the correct environment ID and permitted outbound access?
- Did you inspect the individual tool result, including exit status and stderr?
- Could the original attempt have changed files or called an external service?
- Are you honoring
Retry-Afterand stopping after a defined limit? - Will required files survive environment deletion or replacement?
- Does the retry preserve least-privilege network and credential rules?
This sequence separates request, session, environment, executor and tool failures before you change code or replay an operation. It also keeps a late connection, a completed-but-partially-failed turn and a deleted workspace from being mistaken for a successful run.
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Why does my AI agent time out in the sandbox?
First identify which timeout occurred. An input-time environment connection waits up to five minutes; an idle hosted environment can be deleted after one hour without activity or keep-alives; and a command or tool may fail independently during a turn. Read the structured error, retrieve the session and turn, and check environment state before changing the prompt or retrying.
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Why is my sandbox not connecting?
For a hosted environment, check whether it is still provisioning or has entered failed, then inspect the failure event, packages, attached files, setup commands and redirect destinations. For self-hosting, verify that the executor is running with the correct environment ID, the remote URL is correct, outbound access to the documented OpenAI hosts is allowed, and executor logs match the connection events.
Why did the agent fail while running a tool even though the turn completed?
A completed turn is not proof that every tool succeeded. A mid-turn disconnect can kill a command while the model still returns a final response. Inspect the tool output, exit status, stderr and returned artifacts. Re-read edited files, query external job or API status, or reconcile with an idempotency key before running the operation again.
Should I retry a failed sandbox request?
Only after checking the original session, turn, saved items and side effects. Retry transient connection, overload, rate-limit or temporary service errors with the server’s Retry-After delay and a strict attempt count or deadline. Do not retry unchanged invalid input, bad credentials, billing limits, exhausted budgets or a changed error category.
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Will reusing an environment ID restore files after a timeout or replacement?
No. Reusing an environment ID does not guarantee that files from replacement compute return. A late connection also does not replay input that already timed out, and a process crash does not guarantee recovery of pending input. Store important files in provider storage or snapshots and treat the workspace as replaceable.
Is a local SDK sandbox safe for untrusted commands?
Not automatically. OpenAI’s Agents SDK documentation says Linux UnixLocalSandboxClient runs commands as host processes without OS-level confinement, while macOS filesystem restrictions do not provide network isolation. Use a properly configured Docker, hosted or other external isolation boundary for untrusted commands.
The Bottom Line
Classify the exact error, verify session and environment state, inspect every tool result, and check side effects before replaying work. Hosted and self-hosted sandboxes expose different controls, but neither removes the need for bounded retries, durable storage and least-privilege network access.
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