Fix failing pipelines
Skill a5c-ai/babysitter/.claude/skills/fix-failing-pipelines
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration
npx -y skills add a5c-ai/babysitter --skill fix-failing-pipelinesAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
Copied from the file, not written here
This skill should be used when the user asks to "fix pipelines", "fix CI", "check staging pipelines", "fix failing workflows", "fix failing actions", or wants to find and fix failing GitHub Actions workflows on the staging branch of the babysitter repo.
SKILL.md
4.0 KB, as published. Nobody here has run it
Fix Failing Pipelines
Check GitHub Actions workflows on the staging branch of https://github.com/a5c-ai/babysitter/actions, identify workflows whose most recent run is failing, and dispatch /babysitter:yolo to fix each one.
Workflow
Step 1: Fetch Most Recent Run Per Workflow
Use the gh CLI to list recent workflow runs on the staging branch:
gh run list --repo a5c-ai/babysitter --branch staging --limit 50 --json databaseId,workflowName,status,conclusion,createdAt,headBranch
Group the results by workflowName. For each workflow, keep only the most recent run (by createdAt). Discard workflows where the most recent run is still in_progress -- we only care about completed runs.
Step 2: Identify Failures
From the grouped results, select only workflows where the most recent completed run has conclusion: "failure". Skip workflows whose latest run succeeded, was cancelled, or is still running.
If no workflows have a failing most-recent run, report that all staging pipelines are green and stop.
Step 3: Get Failure Details
For each failing workflow run, fetch the failed job and step details:
gh run view <run_id> --repo a5c-ai/babysitter --json jobs --jq '.jobs[] | select(.conclusion == "failure") | {name, conclusion, steps: [.steps[] | select(.conclusion == "failure") | .name]}'
Then fetch the logs to understand the actual error:
gh run view <run_id> --repo a5c-ai/babysitter --log-failed 2>&1 | tail -100
Step 4: Present Failures
Display the list of failing workflows to the user with:
- Workflow name
- Run ID and link
- Failed job name(s) and failed step name(s)
- Brief summary of the error from the logs
Step 5: Fix via Babysitter
For each failing workflow, invoke the babysitter:yolo skill with a prompt that includes the failure context:
/babysitter:yolo fix the failing "<workflow_name>" pipeline on staging. The most recent run (<run_id>) failed in job "<job_name>" at step "<step_name>". Error details: <brief_error_summary>. Investigate the failure, fix the root cause, and push a fix to the staging branch. Do not create a new branch -- commit directly to staging.
If multiple workflows are failing, process them sequentially -- complete one before starting the next. Present a summary after each fix attempt.
Step 6: Verify Fixes
After pushing a fix for each workflow, wait briefly then check if a new run was triggered:
gh run list --repo a5c-ai/babysitter --branch staging --workflow "<workflow_file>" --limit 1 --json databaseId,status,conclusion
Report whether a new run was triggered and its current status. Do not wait for it to complete -- just confirm it was triggered.
Step 7: Summary
After all failing workflows have been addressed, provide a summary:
- Which workflows were failing
- What was fixed for each
- Whether new runs were triggered
- Any workflows that could not be fixed (with reason)
Notes
- Only the most recent run per workflow type matters. Older failures that have since been superseded by a success are not actionable.
- Runs that are
in_progressare skipped entirely -- they haven't concluded yet. - Cancelled runs are not treated as failures.
- The
ghCLI must be authenticated. If authentication fails, prompt the user to rungh auth login. - Each fix is handed off to
/babysitter:yolowhich handles the actual implementation work non-interactively. - Fixes are committed directly to
staging-- no feature branches or PRs for pipeline fixes. - The entire workflow should be without any user interaction or breakpoints in the run, allowing for seamless pipeline repair.
- if you fixed it, wait for the new run to be completed and check if it succeeded. if it failed again, iterate on the fix until it succeeds.