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Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.
Passed 11 of 17 test cases with the skill, and 4 of 17 without it.
and 12 more in the full report
11 fixed4 passed either way6 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which team handle must be tagged in the bug description section of every generated CI triage issue for Megatron-LM?
| Checked | Without skill | With skill |
|---|---|---|
| Includes @NVIDIA/mcore-oncall in the issue body text. | Missed | Passed |
The instructions your model reads when the skill loads.
Investigate a failing GitHub Actions job, extract the root cause, and file a
well-structured bug issue against NVIDIA/Megatron-LM.
The argument is a GitHub Actions URL. It will be one of:
https://github.com/<owner>/<repo>/actions/runs/<run_id>/job/<job_id>https://github.com/<owner>/<repo>/actions/runs/<run_id>Extract run_id and, if present, job_id.
If a job_id was provided, use that job directly.
If only a run_id was provided, list all failed jobs in the run:
gh run view <run_id> --repo NVIDIA/Megatron-LM --json jobs \
--jq '[.jobs[] | select(.conclusion == "failure") | {id: .databaseId, name: .name, url: .url}]'
If multiple jobs failed, ask the user which one to triage, or triage all of them if they say so.
For each failed job, retrieve the logs and narrow them down to the failure:
# Pull the raw log and keep only error-bearing lines
gh api repos/NVIDIA/Megatron-LM/actions/jobs/<job_id>/logs 2>&1 \
| grep -E "(FAILED|ERROR|\bError\b|assert|Traceback|Exception|##\[error\])" \
| head -200
Also capture the full job name:
test cases passed, vs 4 / 17 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.