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_progress are skipped entirely -- they haven't concluded yet.
Cancelled runs are not treated as failures.
The gh CLI must be authenticated. If authentication fails, prompt the user to run gh auth login.
Each fix is handed off to /babysitter:yolo which 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.

Fix Failing Pipelines

README