AN

analyze-ci

It retrieves and parses failed CI logs to summarize specific errors and failing test cases.

Install

mkdir -p .claude/skills/analyze-ci && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2952" && unzip -o skill.zip -d .claude/skills/analyze-ci && rm skill.zip

Installs to .claude/skills/analyze-ci

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Analyze failed GitHub Action jobs for a pull request.
53 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Fetch logs from failed GitHub Action jobs
  • Identify root causes and specific error messages
  • Extract pytest test names from logs
  • Generate per-job failure summaries
  • Provide paths to raw and failed-step logs

How it works

The skill fetches logs using a package-specific command and then parses the failed-step log to identify root causes and error details.

Inputs & outputs

You give it
URL of a failed GitHub Action job, workflow run, or pull request
You get back
A focused summary containing workflow name, failed step, error context, and log paths

When to use analyze-ci

  • Debug failing pull request CI jobs
  • Summarize root causes of test failures
  • Identify package version issues in builds

About this skill

Analyze CI Failures

Fetch logs from failed GitHub Action jobs and produce a focused per-job failure summary.

Prerequisites

  • GitHub Token: Auto-detected via gh auth token, or set GH_TOKEN.
  • Single-quote URLs when invoking to keep the shell from interpreting ? and other special characters in the URL.

Steps

  1. Fetch logs. Run:

    uv run --package skills skills fetch-logs $ARGUMENTS
    

    The command prints one block per failed job containing the workflow/job name, URL, failed step, and paths to the cached raw log, failed-step log, and (optional) package versions file.

  2. Read each failed-step log and summarize it. For every block, Read the file at its Failed step log: path, then identify:

    • The root cause.
    • Specific error messages (assertion errors, exceptions, stack traces).
    • Full pytest test names where applicable (e.g. tests/test_foo.py::test_bar).
    • A short log snippet showing the error context.
  3. Format each summary with these fields, then a blank line, then the 1-2 paragraph summary.

    • Failed job: <workflow name> / <job name>
    • Failed step: <step name>
    • URL: <job_url>
    • Raw log: <raw_log_path>
    • Failed step log: <failed_step_log_path>
    • Package versions: <package_versions_path> (if present)

    Preserve the Raw log:, Failed step log:, and Package versions: paths verbatim from step 1 so downstream agents can grep deeper.

Invocation examples

# All failed jobs on a PR
/analyze-ci https://github.com/mlflow/mlflow/pull/19601

# All failed jobs in one workflow run
/analyze-ci https://github.com/mlflow/mlflow/actions/runs/22626454465

# Specific job by URL
/analyze-ci https://github.com/mlflow/mlflow/actions/runs/12345/job/67890

# Multiple URLs at once
/analyze-ci https://github.com/mlflow/mlflow/actions/runs/123/job/456 https://github.com/mlflow/mlflow/actions/runs/789/job/012

When not to use it

  • When the job URL is not for a GitHub Action

Prerequisites

GitHub Token

Limitations

  • Requires specific URL formats for GitHub Action jobs
  • Relies on the availability of cached log files

How it compares

Unlike manual log inspection, this skill automatically aggregates failure data and formats it into a structured summary for debugging.

Compared to similar skills

analyze-ci side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
analyze-ci (this skill)12moReviewIntermediate
moai-workflow-testing12moReviewIntermediate
sentry-pr-code-review02moReviewIntermediate
python-testing-patterns772moReviewIntermediate

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