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CI Failure Snapshot

Classify one redacted GitHub Actions failure and get cited evidence plus three bounded next checks before changing workflow code.

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Format: Agent skill, not a browser app. You need an AI agent that can load its instructions and use the required tools.

Package requirements: GitHub Actions run and job JSON exports Python 3.9 or newer on Windows, macOS, or Linux Local files only; no account connection required

You get: Bounded failure-stage classification Exact supplied fields used as evidence

Licence and purchase details

Review the package licence at the destination.

Review the offer and access method at your chosen marketplace. Agensi provides connected-agent access, not a download. Buying a skill does not include an AI-agent subscription or setup service.

Agensi access: This product’s bundled-script workflow through Agensi has not been verified here. Tests of other products do not establish this package’s compatibility. Local setup examples apply to separately obtained downloadable packages.

See tested hosts, versions and workflow limits.

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

What it returns

A representative input and result

fixture-backed sample
input Run conclusion failure; job conclusion failure; steps is empty; no runner name or decisive annotation is supplied.
result Classification: PRE_STEP_FAILURE. Confidence: medium. Inspect annotations, the workflow at the run SHA, runner labels, job conditions, dependencies, reusable workflows, and matrix siblings before changing code.

Access and approval boundaries

Known limitations

// choose with context

Is CI Failure Snapshot the right skill?

Best fit

A job can fail or wait before normal steps appear, leaving the owner unsure whether to inspect runners, policy, platform state, or workflow code.

It returns

Bounded failure-stage classification. Exact supplied fields used as evidence.

Do not use it as

An empty steps array is missing execution evidence, not proof that a secret or application code failed.

Compatibility, access, version, and licence

Reads or accesses
Declared local scope: run.json, job.json, ci-snapshot/**.
Compatibility
GitHub Actions run and job JSON exports Python 3.9 or newer on Windows, macOS, or Linux Local files only; no account connection required
Version
1.0.0
Licence
Review the package licence and seller terms at the linked destination.

What happens next

Open the Agensi listing, check the current offer and connect a supported agent. Agensi loads the skill through its connector; it no longer provides a download. Approve any purchase before use. Check Agensi’s current connection guide before changing an existing connection.

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.

Get CI Failure Snapshot on Agensi