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1. Find the failed run and identify its stage
- Open the repository’s Actions tab, choose the workflow, and select the failed run.
- Read the summary and job graph. Determine whether the problem occurred before a job started, during job setup, in a particular action or shell step, or while the job was completing.
- Open the affected job. Failed steps are expanded in the run logs; select other steps when you need to compare their output or establish what ran beforehand.
GitHub’s workflow run log documentation describes the run page, searchable logs, downloadable log archive, and permalinks to individual log lines. A permalink is useful when asking a teammate to review the same error without making them hunt through the run.
2. Read the failing step and match it to the workflow YAML
In the failed step, look for the earliest specific error rather than assuming the final line is the cause. Read the surrounding output: earlier warnings, commands, environment details, or a failed download can explain a later generic exit code. Use the log search when the output is long, and download the archive if the run page does not show the details you need.
Then open the workflow file from the exact commit used by the run. Check the command, action version, inputs, environment variables, working directory, and any preceding steps that supply files or credentials. Comparing against the current branch instead of the run’s commit can lead you to debug a version of the workflow that never produced the failure.
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For a failure that appears on each new commit, check whether the workflow file under .github/workflows has invalid syntax or structure. If the run never reaches a job, investigate workflow parsing and trigger configuration before changing a shell command.
3. Use setup logs to check runner assumptions
Each job log includes Set up job and Complete job entries. Expand Set up job and inspect its details when the failure may involve the environment rather than your script. For GitHub-hosted runners, setup output includes runner-image information and a link to the image’s preinstalled software.
Compare that environment with what the workflow expects: tool versions, executable paths, operating system behavior, and software availability. This is especially useful when a workflow begins failing after relying on a version or tool that is no longer present or is different from the one assumed.
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4. Diagnose skipped or unexpected jobs and steps
For job-level conditions
If a job was skipped or ran when it should not have, download the job log archive and open JOB-NAME/system.txt, replacing JOB-NAME with the job’s name. GitHub records the condition evaluation as Evaluating, Expanded, and Result. The expanded expression shows context values resolved at runtime; compare those values and the final result with the condition you intended.
These evaluation details cover job-level conditions. They do not provide the same explanation for a step-level if condition.
For step-level conditions or unclear expression behavior
Enable step debug logging as described below, then inspect the step’s additional output. This is the appropriate escalation when the issue concerns a step condition or the regular logs do not show why an action behaved as it did.
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5. Enable debug logging when regular logs are not enough
GitHub’s debug logging guide says that additional logging can help when workflow logs do not provide enough detail to diagnose unexpected workflow, job, or step behavior. There are two different settings:
ACTIONS_STEP_DEBUG=trueadds more detail to step logs, including useful context for action and step behavior.ACTIONS_RUNNER_DEBUG=trueadds runner and worker process diagnostic logs to the log archive. Use it when investigating runner startup, coordination, or execution questions.
You can configure these as repository or environment secrets or variables, subject to the permissions and access requirements for the repository or environment. GitHub also lets eligible reruns enable debug logging. Review logs and archives before sharing them: diagnostic output can expose operational details.
6. Check tool-specific, platform, and operational causes
Not every failure is caused by workflow logic. GitHub’s workflow troubleshooting guide also covers billing, runner, and network issues. Once the failing stage is clear, consider whether the evidence points to a platform or operational problem rather than changing the workflow speculatively.
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A command-line tool may also have its own verbose mode. GitHub’s troubleshooting examples include npm install --verbose for npm and GIT_TRACE=1 GIT_CURL_VERBOSE=1 git ... for Git. Use a tool’s diagnostic options when its output is the part you cannot explain, and handle the resulting logs with the same care as Actions logs.
7. Rerun deliberately—not as proof of a fix
A rerun can help confirm a change or capture additional details, but it is not a new run under the current user’s identity. GitHub uses the original triggering actor’s privileges and the original GITHUB_SHA and GITHUB_REF. A rerun therefore does not test a newer commit unless that commit is the one referenced by the original run.
From the run page, GitHub offers options to rerun all jobs, failed jobs, or a specific job. With GitHub CLI, rerun failed jobs with debug logging using:
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gh run rerun RUN_ID --failed --debug
Replace RUN_ID with the run’s ID. GitHub Docs states that a workflow can be rerun for up to 30 days after the initial run, with a maximum of 50 reruns. A rerun that succeeds does not by itself show that the underlying issue is fixed; failures that depend on timing, network conditions, or other changing factors may not reproduce consistently.
Choose the diagnostic that matches the symptom
| Diagnostic | Best for | What it provides |
|---|---|---|
| Run summary, graph, and existing logs | Locating the failed job or step | Fast first check; logs can be searched or downloaded, and a specific line can be shared by permalink. GitHub Docs. |
system.txt condition details |
A job that skipped or ran unexpectedly | Job-level expression, expanded runtime values, and result. Does not cover step-level conditions. GitHub Docs. |
ACTIONS_STEP_DEBUG=true |
Sparse step or action output; step-level behavior | More detailed step logs. GitHub Docs. |
ACTIONS_RUNNER_DEBUG=true |
Runner startup, coordination, or execution questions | Runner and worker process logs in the archive. GitHub Docs. |
| Rerun with or without debug logging | Testing the original run again or collecting more detail | Can rerun all, failed, or selected jobs; retains the original run’s SHA, ref, and triggering actor’s privileges. GitHub Docs. |
Turn the evidence into a fix
Use the failing stage to narrow the next change: correct workflow syntax or triggers when no job starts; adjust environment assumptions when setup output conflicts with the YAML; fix the command or action identified by the step log; and revise a condition only after checking its runtime values. If the logs instead point to billing, runner, or networking, address that operational cause. After a change, verify it with a run on the intended commit and inspect its logs rather than treating a successful rerun of the old commit as confirmation.
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