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When an AI agent API call fails, first identify the status and exact error code; then decide whether the cause is a temporary throttle, an account limit, or a timeout. Before retrying, check the response’s Retry-After value, find out whether your SDK already retries, and verify whether the agent completed any work. Retry only transient failures, with bounded attempts and an overall deadline.
Start with this decision tree
- Identify what failed. Record the HTTP status, exact error type and code, request ID, elapsed time, and whether cancellation or a deadline occurred. For a stream, inspect the stream events as well as the HTTP status.
- If the response is 429, classify the reason before retrying. A temporary request- or token-rate limit may call for a delayed retry. An exhausted credit balance or organization usage limit needs an account or usage change, not repeated requests. See OpenAI’s troubleshooting guide for API rate limits and 429 errors.
- If it is a transient rate limit, inspect
Retry-After. If the response contains a valid delay, wait at least that long. If it is missing or invalid, use exponential backoff with jitter, and bound both attempts and total retry time. See OpenAI’s rate-limit guidance. - Check who owns retries. Inspect the installed SDK’s version and retry configuration before adding an application-level loop. Two retry layers can multiply attempts.
- If the call timed out or the connection dropped, check the agent’s outcome before resubmitting. A client-side failure does not prove the server did no work. Confirm whether the session or turn exists, whether it completed, and whether it triggered external actions.
- Stop at the operation deadline. A per-attempt network timeout is not the same as a deadline for the whole agent operation, including backoff and retries.
Capture enough evidence to explain the failure
Useful debugging starts with a record for each attempt, not just a log line saying “request failed.” Capture enough context to match the failure to the provider’s logs, distinguish a slow attempt from a retry delay, and determine whether another component retried the same operation.
Record these fields for every attempt
- Request context: provider, endpoint or API surface, model, and relevant agent configuration. Avoid logging secrets or sensitive prompt content; record a safe identifier or redacted summary if needed.
- Client context: SDK name and installed version, retry settings, and whether your own application or another service also retries.
- Timing and control flow: attempt number, timestamp with timezone, elapsed time, per-attempt timeout, overall deadline, and whether cancellation or deadline expiry stopped the operation.
- Failure details: HTTP status, exact error type, code and message, and whether the failure came from the HTTP response, a stream event, a client exception, cancellation, or a timeout.
- Provider diagnostics: request ID and relevant response headers, including rate-limit information and
Retry-Afterwhen present. - Agent outcome: session or turn identifier and the last known state, including whether tools or external actions had already run.
OpenAI’s troubleshooting guidance calls for retaining the exact error, code, request IDs, time with timezone, and relevant limit information. Its API overview describes response headers as a place to find unique request IDs and rate-limit details. These values make it easier to distinguish separate failures and provide actionable information when escalating a persistent issue.
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Classify a 429 before deciding to retry
A 429 is a status code, not a complete diagnosis. In particular, do not treat every 429 as proof that sending the same request again after a short pause will work. Read the provider’s error code and message, then identify which condition the response describes.
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Temporary request or token rate limit
A temporary throttle means requests or token use are arriving faster than the applicable limit permits. Use the response’s Retry-After hint if it is valid, and reduce the pressure causing the throttle when the evidence points to bursts, concurrency, or token volume. Unsuccessful requests can count toward per-minute limits, so immediate repeated submissions may make the problem worse.
Request and token pressure are not identical. If the error indicates token pressure, inspect prompt size and the output-token allowance rather than assuming that reducing request frequency alone will address it. OpenAI’s 429 troubleshooting guidance notes that long prompts and unnecessarily large output-token allowances can contribute to token-rate errors.
Credit or organization usage limit
OpenAI documents credit_balance_exhausted and organization_usage_limit_exceeded as conditions that can also produce a 429. These are not temporary throttles to solve by retrying the same call. Investigate the indicated credit or organization usage condition and address it before expecting a repeated request to succeed. The error code and message, rather than the status alone, should drive that decision.
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Do not put billing, quota, credential, or invalid-request failures into an automatic retry loop. A retry is useful only if waiting can plausibly change the condition. If a request must be corrected or an account condition resolved, retrying without making that change adds traffic without addressing the cause.
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Retry transient failures without multiplying traffic
For a temporary rate limit, honor a valid Retry-After delay as a minimum wait. If no usable server delay is present, exponential backoff increases the wait after successive unsuccessful attempts; jitter adds a random component so a group of clients is less likely to retry in lockstep. OpenAI describes it this way: “Exponential backoff means waiting briefly after an unsuccessful request, then increasing the delay after each unsuccessful retry.” See the rate-limit documentation.
Use one bounded retry policy
- Decide which failures are eligible. Retry only errors you have classified as transient. Do not infer retryability from the status code alone.
- Check the server hint. When a valid
Retry-Afteris supplied, do not retry before that delay has passed. When it is absent or invalid, use exponential backoff with jitter. - Set an attempt limit. Choose a finite maximum number of attempts for the operation. The appropriate value depends on the provider, SDK, application and latency requirements; there is no universal retry count in the guidance covered here.
- Set a total time budget. Include attempt timeouts and all waiting periods in the operation’s deadline. Do not let each retry restart an unlimited clock.
- Account for SDK retries. Determine whether the SDK already retries the response. Either include those retries in your total policy or configure a single layer to own retries; do not unknowingly stack independent loops.
- Stop when the deadline expires or the operation is cancelled. Surface that outcome distinctly from an HTTP rate-limit response so operators can tell what actually ended the work.
The SDK’s automatic retry behavior is part of the effective policy, even if application code never calls a retry function. OpenAI says its official SDKs automatically retry eligible 429 and 503 responses; how long they handle server-supplied delays can vary with SDK version and configuration. Anthropic’s error documentation says its official SDKs retry transient failures such as connection errors, rate limits, and 5xx errors with exponential backoff, honor retry-after when present, and retry twice by default. Treat that count as a documented SDK default, not as a universal rule: check the installed version and its configuration. See OpenAI’s TypeScript and JavaScript library documentation and Anthropic’s API error documentation.
Reduce the cause, not just the symptom
- If requests arrive in bursts, smooth submissions or reduce concurrency where your logs show that requests are reaching the limit together.
- If the provider reports token pressure, examine prompt length and whether the requested output allowance is larger than the task needs.
- If retries continue to receive the same account or usage error, stop retrying and resolve the underlying condition.
- If many clients retry at once, jitter helps disperse their retry timing, but it does not increase the provider’s limit or make an ineligible error transient.
Rate limits can vary by provider, endpoint, model, organization, and account configuration. Avoid baking a static quota assumption into a general retry handler; use current account-specific information and the response diagnostics available for the request.
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Keep attempt timeouts separate from the agent deadline
A per-attempt timeout limits how long one network attempt can take. An operation deadline limits the full unit of work: attempts, retry waits, and any remaining agent processing. If an application gives every retry a fresh full timeout without enforcing an overall deadline, total latency can grow beyond what the caller intended.
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Track both clocks. When a network attempt times out, decide whether the operation still has time to retry; when the overall deadline expires, stop even if the retry count has not been exhausted. Handle cancellation and deadline expiry as their own outcomes. They can stop the work without producing an HTTP 429, so logging them as rate limits obscures the actual failure.
For long-running requests and streams
Anthropic documents a 504 timeout_error for a request that times out while processing, and suggests considering the streaming Messages API for long-running requests. Streaming changes how clients must detect failures: an SSE error can arrive after the API has returned HTTP 200. A successful HTTP status therefore does not establish that the stream finished successfully. Process and validate stream events through completion rather than treating the initial response status as the final result. These are Anthropic-specific documented behaviors, not a universal contract for every provider or endpoint; see its error documentation.
After a timeout or lost connection, verify whether the agent did the work
A timeout describes what the client observed, not necessarily what happened on the server. The request may have failed before it was accepted, may still be processing, or may have completed even though the response did not reach the client. In an agent workflow, blindly submitting the same instruction again can repeat a tool call or external action.
- Look up the existing session or turn. Use the identifiers your application recorded to determine whether the operation was created and whether it remains active.
- Inspect its latest state and completed actions. Establish whether the model finished, whether tools ran, and whether any external side effect already occurred.
- Choose recovery based on that state. Resume or reconcile an in-progress operation where the API supports it; do not create a duplicate merely because the original client request timed out.
- Retry only after you know what is safe to repeat. If an action may have completed but its outcome is unknown, verify or reconcile it before resubmitting.
OpenAI’s Agents API errors and recovery guidance advises checking the outcome and completed actions before retrying after connection failures, request timeouts, or service errors. This matters most when the agent can change data, send a message, place an order, or trigger another non-repeatable action.
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Provider-specific signals are useful, but not interchangeable
The following comparison summarizes the documented behaviors described in the linked provider materials. It is not a shared status-code contract: parse errors according to the provider and endpoint actually in use.
| Diagnostic area | OpenAI | Anthropic |
|---|---|---|
| 429 interpretation | Temporary request or token rate limits must be distinguished from credit exhaustion and organization usage limits by inspecting error details. See the 429 troubleshooting guide. | A 429 can represent rate-limit or spend/usage conditions. Inspect the error and follow the provider’s retry guidance. See Claude API errors. |
| Retry guidance and SDK behavior | For temporary rate limits, use a valid Retry-After as a minimum wait; otherwise use bounded exponential backoff with jitter. Official SDKs automatically retry eligible 429 and 503 responses, but handling of long server delays varies by SDK version and configuration. See rate limits and the TypeScript and JavaScript library documentation. |
Official SDKs retry transient failures including connection errors, rate limits, and 5xx errors with exponential backoff. The error documentation states two retries by default and says the SDK honors retry-after when present; verify the installed SDK version. See Claude API errors. |
| Timeout and overload signals | Agents recovery guidance covers connection failures, request timeouts, and service errors; it calls for checking operation outcome before retrying. See Errors and recovery. | The error documentation identifies 504 as timeout_error and 529 as overloaded_error. It also warns that an SSE error may occur after HTTP 200. See Claude API errors. |
| Request diagnostics | Response headers can provide unique request IDs and rate-limit details. See the API overview. | The error documentation describes request IDs and advises including the ID when contacting support about persistent failures. See Claude API errors. |
A practical incident checklist
Use this checklist when a failure is recurring or when you need to hand the issue to another engineer:
- Preserve the original attempt: exact error body or safe redacted equivalent, status, request ID, timestamp with timezone, and relevant headers.
- Identify the software actually running: provider, endpoint, model, SDK and version, and every configured retry layer.
- Classify before tuning: transient rate limit, credit or usage condition, timeout, stream error, cancellation, or another request/client failure.
- Check whether the server supplied a wait: record
Retry-Afterand do not retry sooner than a valid indicated delay. - Inspect rate pressure: correlate attempts with bursts, concurrency, and prompt/output-token size; reduce the source of pressure when indicated.
- Audit retry multiplication: calculate the effective behavior across SDK, application, queue, and caller rather than considering only one loop.
- Enforce two bounds: maximum attempts and an overall operation deadline that includes backoff.
- Reconcile agent state after uncertain failures: inspect sessions, turns, and completed actions before repeating work.
- Escalate with identifiers: include the request ID, exact error/code, timestamp and timezone, relevant headers, endpoint, and SDK version for a persistent provider-side failure.
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Retrying every 429
The status alone does not distinguish temporary rate pressure from exhausted credits or an organization usage limit. Read the code and message before choosing a retry policy.
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Rapid repeated attempts can add pressure, and unsuccessful requests can count toward per-minute limits. Use the server’s valid delay when supplied; otherwise back off with jitter.
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Adding an application loop without checking the SDK
Automatic SDK retries can be invisible at the call site. If the SDK retries and the application retries the SDK call, effective attempts and elapsed time can grow unexpectedly. Inspect the installed version and settings, then make retry ownership explicit.
Treating an attempt timeout as the whole-operation deadline
Each network attempt may respect its own timeout while retries and backoff continue beyond the caller’s useful time budget. Enforce a separate operation deadline and record which limit ended the work.
Assuming timeout means no side effects
A lost response leaves the outcome uncertain. Check the agent’s state and completed actions before sending an instruction that could cause duplicate work.
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For Anthropic streaming, an SSE error can follow an HTTP 200 response. Consume and interpret stream events through completion rather than concluding success from the initial status alone.
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