analyze-ci

# Analyze CI Failures Fetch logs from failed GitHub Action jobs and produce a focused per-job failure summary. URLs provided: $ARGUMENTS If no URLs are listed above, ask for a job, run, or PR URL and stop. `fetch-logs` requires at least one and exits 2 without. ## Prerequisites - **GitHub Token**: Auto-detected via `gh auth token`, or set `GH_TOKEN`. ## Steps 1. **Fetch logs.** Run, single-quoting each URL so the shell does not interpret `?` or other special characters in it: ```bash uv run --package skills skills fetch-logs '<url>' ['<url>' ...] ``` 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 ```bash # 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 ```