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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWhen a GitHub API request is throttled, inspect its response headers and body, then wait according to GitHub’s guidance before retrying. Do not treat every 403 or 429 alike, and do not rerun an entire GitHub Actions workflow just because one API call failed. A shared request queue can help agent workers avoid collectively overloading the API; workflow reruns are a separate recovery choice for failed jobs or runs.
What rate limits apply to a GitHub-based agent workflow?
GitHub has primary rate limits tied to authentication and the API resource, as well as secondary limits intended to constrain request patterns and resource consumption. There is no single hourly limit that applies to every GitHub API client. The figures below are values in GitHub’s current documentation, accessed in 2026; the documentation pages do not state publication dates, and GitHub may change the limits without notice.
| Limit or signal | Documented value or behavior | What it means for an agent workflow |
|---|---|---|
Actions GITHUB_TOKEN primary limit |
1,000 requests per hour per repository; 15,000 per hour per repository for requests to resources belonging to a GitHub Enterprise Cloud account. | Apply the value relevant to the token and resource. Do not assume the Enterprise Cloud figure applies to every request made from an Enterprise Cloud repository. |
| Concurrent API requests | No more than 100 concurrent requests across REST and GraphQL. | Workers that fan out requests can exceed this collectively, even if each worker is modest on its own. |
| Request points | 900 points per minute for REST endpoints and 2,000 points per minute for the GraphQL endpoint. | Point costs vary by request; request count alone does not describe all secondary-limit pressure. |
| Other secondary-limit factors | GitHub also considers CPU time, content creation, and other conditions that may not be disclosed. | A request may be throttled even when the client has not exhausted its primary hourly allowance. |
These are policy values, not service guarantees. GitHub says some endpoints may have lower limits and secondary limits can be triggered for undisclosed reasons. See GitHub Docs, “Rate limits for the REST API,” for the live figures and definitions.
How can a client tell why a request was throttled?
Use the response headers for primary-limit status
REST responses include headers for the limit, the amount used, the remaining allowance, the reset time in UTC epoch seconds, and the resource family. For the request’s primary-limit status, use those response headers as the live signal. GitHub notes that requests can be processed across regions and header values may vary, so pace from the actual response rather than relying on a predicted, exact remaining count.
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Read the status, headers, and body together
Rate-limit failures can arrive as 403 Forbidden or 429 Too Many Requests. A primary-limit response has x-ratelimit-remaining: 0; a secondary-limit response includes an explanatory message. The status code alone does not tell you which wait strategy to use. Preserve and inspect the headers and response body when a request fails.
Use GET /rate_limit as an overview, not a throttle detector
GET /rate_limit summarizes resource-family allowances and does not use primary allowance, but it may count against secondary limits. It can also disagree with headers on an individual response. GitHub provides no endpoint that directly reports whether a client is under a secondary limit, so this request cannot replace response-based handling.
When should an agent retry a 403 or 429?
Follow GitHub’s documented wait order. Each delay is a minimum: do not retry sooner because a local timer or worker happens to be ready.
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- If
retry-afteris present: wait at least the number of seconds in that header. - Otherwise, if
x-ratelimit-remainingis zero: wait until the UTC epoch time inx-ratelimit-reset. - Otherwise: wait at least one minute before retrying.
- If a secondary-limit failure continues: increase the delay exponentially between attempts and stop after a defined retry limit. GitHub’s “Troubleshooting the REST API” advises waiting an exponentially increasing amount of time and throwing an error after a specific number of retries; it warns that continuing to make requests while limited can risk an integration ban.
Make the retry limit explicit in the client or workflow. When it is reached, return a clear failure with the response details rather than silently dropping the task or retrying forever. Do not retry every error as if it were throttling: an authorization, permission, or missing-resource problem will not be fixed by waiting.
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Before retrying a request that creates or changes data, decide whether repeating it could create a duplicate or other unwanted side effect. This idempotency check is an engineering safeguard, not a guarantee supplied by GitHub’s rate-limit guidance. If the client cannot establish that a mutation is safe to repeat, surface the failure for diagnosis rather than replaying it blindly.
How can multiple agents avoid throttling one another?
GitHub recommends authenticated API calls, serial rather than concurrent requests to avoid secondary limits, and a pause of at least one second between large numbers of mutative POST, PATCH, PUT, or DELETE requests. Authentication generally provides a higher primary allowance, but it does not remove secondary limits.
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Coordinate requests across workers
A shared queue or rate limiter is a practical design inference from GitHub’s serialization advice, not a GitHub-prescribed architecture. Have workers submit API work to a coordinator that can limit simultaneous calls, apply the one-second spacing to large volumes of mutations, and pause a credential or resource group when a response supplies reset guidance. If every agent maintains its own independent schedule, their combined traffic may exceed a limit even when no worker appears to be sending requests rapidly.
- Keep the response headers and body attached to failed requests so the coordinator can choose the correct delay.
- Group traffic by the credential and resource it uses where practical; separate tokens do not make a single workflow’s requests exempt from shared secondary constraints.
- Allow parallel work only where requests are independent and concurrency is appropriate; serialize requests when they compete for a shared limit or cause side effects.
Check token scope and permissions before waiting
In GitHub Actions, use GITHUB_TOKEN when it is suitable, and grant only the permissions the workflow needs with the workflow’s permissions key. That token applies to repository-owned resources where the workflow runs. Access to another repository or organization may require a separately authorized credential, such as a GitHub App token or personal access token. Check the credential and its permissions before treating a 403 or 404 as a transient rate-limit failure. See GitHub Docs, “Using the GITHUB_TOKEN for authentication in workflows.”
Should you retry an API call or rerun a GitHub Actions workflow?
Choose the recovery scope that matches the failure. An API retry repeats an individual operation after a suitable wait. A workflow rerun re-executes jobs from a run and can repeat their side effects. A rate-limited API call does not by itself mean that the whole workflow should be replayed.
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| Recovery action | Use it when | What it repeats |
|---|---|---|
| Retry one API operation | The response indicates throttling, the wait has elapsed, and repeating the operation is safe. | The API request, not the whole job or workflow. |
| Rerun failed jobs | Logs show that failed jobs need another attempt and their work is safe to repeat. | Failed jobs, rather than every job in the run. |
| Rerun selected jobs | A specific job needs recovery and other completed work should remain untouched. | The selected job or jobs. |
| Rerun the workflow | The failure requires repeating the run as a whole. | The full workflow run; review side effects before doing so. |
GitHub allows a workflow run to be rerun within 30 days of its initial run and caps a run at 50 reruns. A rerun uses the privileges of the actor who first triggered the workflow and retains the original event’s GITHUB_SHA and GITHUB_REF; it is not a new run against the latest commit.
With GitHub CLI, use gh run rerun RUN_ID to rerun a run, gh run rerun RUN_ID --failed to rerun failed jobs, or gh run rerun RUN_ID --job JOB_ID to rerun a selected job. These choices affect what work is repeated, so inspect the run before issuing a command.
What should you inspect before recovering a failed workflow?
Read the failed job’s logs
Use the Actions logs to identify the step that failed; GitHub supports searching and downloading logs. Establish whether the failure was a rate-limit response, a permission or configuration problem, or a failure in the workflow’s own code before deciding to retry or rerun. Replaying a job without diagnosing its failure can repeat work without addressing the cause.
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Check what happened to dependent jobs
Jobs that need a failed or skipped prerequisite are skipped unless their conditions explicitly allow them to continue. If a workflow needs cleanup or reporting after a failure, configure those conditions deliberately, and ensure they do not unintentionally keep work running after cancellation. A skipped dependent job is not automatically evidence that it should be rerun in isolation.
Control overlapping workflow runs when side effects matter
Actions allows multiple jobs and workflow runs to execute concurrently by default. A concurrency group can limit overlapping work. By default, a group has only one pending run; a newly pending run cancels the previous pending run. Configure queuing if all pending work must execute in order. This is useful when duplicate deployments, agent commits, or other concurrent side effects would be harmful, but independent work can remain concurrent when that is safe. See GitHub Docs, “Control the concurrency of workflows and jobs.”
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