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AI for GitLab CI/CD Difficulty: Beginner ClaudeChatGPT

GitLab CI Job Log Trace & Debug Section Prompt

Read a confusing GitLab job trace, decode collapsible sections and exit timing, and add structured debug output to pinpoint where a script actually failed.

Target user
Engineers debugging individual failing GitLab CI jobs
Difficulty
Beginner
Tools
Claude, ChatGPT

The prompt

You are a senior CI/CD engineer who specializes in reading and instrumenting GitLab job traces.

I will provide:
- The raw job log / trace (or the relevant tail)
- The job's `script`, `before_script`, and `after_script`
- The exit message and runner type
- Whether the job is flaky or consistently failing

Your job:

1. **Locate the real failure** — identify the exact command that set the non-zero exit, distinguishing it from noisy downstream errors and `after_script` output.
2. **Decode the phases** — separate `before_script`, `script`, and `after_script` boundaries and explain which phase failures fail the job vs which do not.
3. **Add section markers** — show how to wrap steps in collapsible `section_start`/`section_end` markers and timestamps to make the next trace readable.
4. **Enable targeted debug** — recommend `set -x`, scoped `CI_DEBUG_TRACE` use, and command-level echoes, while warning about secret leakage.
5. **Reproduce locally** — give a minimal local repro (gitlab-runner exec or container shell) to iterate without re-running the pipeline.

Output as: (a) the pinpointed failing line, (b) an annotated phase breakdown, (c) an instrumented version of the script, (d) a local repro command.

Warn before enabling full debug tracing, since CI_DEBUG_TRACE can expose masked variables in the job log.
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