CI Failure Snapshot
Classify one redacted GitHub Actions failure and get cited evidence plus three bounded next checks before changing workflow code.
What problem does CI Failure Snapshot solve?
A job can fail or wait before normal steps appear, leaving the owner unsure whether to inspect runners, policy, platform state, or workflow code.
Use it to
- Triage an empty-steps GitHub Actions job
- Separate runner wait from completed failure
- Catch contradictory run and job exports
- Choose the next evidence check before editing YAML
What it returns
- Bounded failure-stage classification
- Exact supplied fields used as evidence
- Three next read-only checks
- Confidence and explicit unknowns
A representative input and result
Access and approval boundaries
- Read access only to the user-supplied local input files.
- Write access only to the selected local output directory.
- No browser, network, credential, account, or environment-variable access is required.
Known limitations
- An empty steps array is missing execution evidence, not proof that a secret or application code failed.
- The snapshot does not inspect a repository, connect to GitHub, rerun CI, or change workflow files.
- Provider metadata can remain inconclusive and is then labeled unresolved.
Questions
Does it connect to GitHub?
No. It reads redacted local JSON supplied by the user.
What does an empty steps array mean?
It means normal execution evidence is absent. It does not prove a secret or application code failed.
Can it classify a normal step failure?
Yes. A recorded failing step takes precedence over pre-step inference.
Does it edit workflow YAML?
No. It returns next checks only.
Can it diagnose every platform incident?
No. It labels unsupported or contradictory evidence unresolved.
When should I use CI Doctor?
Use the paid CI Doctor when the next job requires repository, workflow-revision, annotation, matrix, manifest, or related-run inspection.
CI Failure Snapshot keeps proof and approval boundaries visible.
The listing includes the tested package, realistic samples, declared permissions, and known limitations.
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