Fix Failing Pipelines logo

Fix Failing Pipelines

OrganizationPopular
a5c-ai
fix-failing-pipelines

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.

Overview

Publishera5c-ai
Repositorybabysitter
Skill namefix-failing-pipelines
Stars
1.8K
Forks
112
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by a5c-ai on GitHub. Read the source before you install it.

Installation

Install the Fix Failing Pipelines AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/a5c-ai/babysitter/tree/main/.claude/skills/fix-failing-pipelines
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/a5c-ai/babysitter.git /tmp/babysitter
mkdir -p .claude/skills
cp -r /tmp/babysitter/.claude/skills/fix-failing-pipelines .claude/skills/fix-failing-pipelines
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fix Failing Pipelines in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fix Failing Pipelines on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fix Failing Pipelines is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

bash
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:

bash
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:

bash
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:

bash
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.

Frequently asked questions

What does the Fix Failing Pipelines AI skill do?

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.

Why use Fix Failing Pipelines on TypingMind?

Because you install it once and use it with any model. Fix Failing Pipelines is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fix Failing Pipelines in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/a5c-ai/babysitter/tree/main/.claude/skills/fix-failing-pipelines. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Fix Failing Pipelines?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fix Failing Pipelines?

As many as you like. As long as a model supports skills, you can use Fix Failing Pipelines with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fix Failing Pipelines AI skill free?

Yes. It is published on GitHub by a5c-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇