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    🩺 CI Doctor

    2

    Diagnose CI step failures and jobs that fail before steps run. Trace empty-step states and matrix cancellations to evidence, then propose the smallest reviewable fix.

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    🩺 CI Doctor

    🩺 CI Doctor

    Example session with this skill installed

    Use $ci-doctor to diagnose why GitHub Actions job 123456789 failed with steps: []. Tell me the next safe check, but do not change files or rerun CI.

    • Read your context and instructions
    • Compiled the ci doctor

    Run State: GitHub Actions / initialize; conclusion: failure; normal steps: none. Root Cause: unresolved pre-step failure. Evidence: the job exposes an empty steps list, no runner assignment, and no decisive annotation. Fix: inspect the workflow at the run SHA and the check-run annotations. Confidence: low until those artifacts are available. Approval Boundary: no code, secret, or workflow change is justified yet.

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    About this skill

    Diagnose the failure before editing CI

    CI Doctor turns a failed pipeline into one evidence-backed diagnosis, a bounded fix, and a clear approval boundary. It starts with GitHub Actions and recognizes GitLab CI and CircleCI markers from supplied configuration and logs.

    Handles failures with no steps or logs

    When a job exposes no normal steps or an empty steps array, CI Doctor does not guess that application code or a secret failed. It inspects run and job state, annotations, the workflow at the failing commit, runner assignment and labels, environment protections, job conditions and dependencies, reusable workflows, and matrix siblings. If the evidence remains incomplete, it reports an unresolved pre-step failure and names the next read-only check.

    Understands matrix behavior

    CI Doctor traces fail-fast cancellations back to the earliest required sibling failure and distinguishes job-level allowed failures from step-level continue-on-error behavior. It preserves intentional experimental jobs rather than turning required failures green.

    Evidence first, mutations by approval

    • Inspects workflow YAML, manifests, lockfiles, tests, diffs, logs, and run metadata.
    • Separates the primary cause from cascading errors and cancelled matrix siblings.
    • Returns run state, root cause or explicit uncertainty, short evidence, the smallest fix or next check, and confidence and unknowns.
    • Never treats a secret reference or empty step list as proof that a secret is missing.
    • Asks before editing files, rerunning CI, setting secrets, committing, pushing, or opening a pull request.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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