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Ci Fixer

Community
hex
ci-fixer

A CI job fails on a named revision and the fix belongs in code, config or tests, not in the CI provider.

Overview

Publisherhex
Repositoryclaude-council
Skill nameci-fixer
Stars
866
Forks
106
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 hex on GitHub. Read the source before you install it.

Installation

Install the Ci Fixer 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/hex/claude-council/tree/main/mods/council-pane/specialists/ci-fixer
  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/hex/claude-council.git /tmp/claude-council
mkdir -p .claude/skills
cp -r /tmp/claude-council/mods/council-pane/specialists/ci-fixer .claude/skills/ci-fixer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ci Fixer 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 Ci Fixer 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 Ci Fixer 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.

CI Fixer

Make one failing CI job pass for the right reason. A green run earned by retrying, skipping or loosening a check is a failure of this task, not a success.

Pin the failure

  1. Work from the exact revision SHA, run ID and job named in the task. If the task names only a pull request or a branch, ask for them in the report rather than guessing which run is current.
  2. Check that the run is still relevant. A cancelled run is often superseded by a newer run on the same revision or branch. If the newest run passes, stop and report that.
  3. Fetch the failed job's log once and keep it. Work from that copy. Prefer the job's own status over a summary or rollup view.
  4. Find the first real error, not the last line. Later errors are often consequences.

Classify before changing anything

Put the failure in exactly one class and record the evidence for it:

  • product: the code under test is wrong. The same failure should reproduce locally or in CI's environment.
  • test harness: the test, fixture, helper or setup is wrong, flaky or order-dependent, and the product is fine.
  • environment: runtime version, OS difference, missing tool, dependency resolution, disk, network, cache. The code and test are fine on another environment.
  • credential: a secret, token, quota or permission is missing or expired. This is never fixable in code. Stop and report which credential and where the log shows it.

If the evidence does not settle the class, say so and report what would.

Reproduce

  • Run the failing command locally with the same arguments the job used.
  • If it passes locally, do not conclude the CI is wrong. Match CI's OS, runtime version, locale, timezone and environment variables, as far as you can, and try again. A local pass does not override a CI failure.
  • For a suspected flake, run the single test repeatedly and record the pass and fail count. Flaky means you saw it fail and pass on the same code.

Fix

  • Fix the class you identified:
    • product: fix the code at the root cause, as a bug fix;
    • harness: fix the test or fixture so it is deterministic, keeping what it asserts;
    • environment: pin or update the version, cache key, or setup step in the repo's CI config.
  • Never skip, disable, mark as expected-failure, raise a timeout without a measured reason, loosen an assertion, or add a retry loop to make the job pass.
  • Keep changes to the job's failure. Record unrelated failures you notice in the report rather than fixing them.

Prove it

  • Run the reproduction again and show it passing.
  • For a flake fix, repeat the run enough times that the previous failure rate would have shown at least one failure, and record the count.
  • State plainly that the CI run itself has not re-run on your change. The tool records your work; CI results come afterwards.

Evidence to record

  • Revision, run ID, job name, and the first real error line.
  • The class and why.
  • Local reproduction command and its output, before and after.
  • For flakes: repeat counts before and after.

Stop conditions

Stop and report when the failure is a credential or provider-side problem, when the newest run already passes, when you cannot reproduce and cannot match CI's environment, or when the fix needs a change outside the repo.

Handoff

Report the class, the root cause, the change, the proof commands with results, and what still needs a real CI run to confirm.

CI triage steps adapted from openclaw's openclaw-testing and release-openclaw-ci skills (MIT, OpenClaw Foundation); see ../LICENSE-openclaw.

Frequently asked questions

What does the Ci Fixer AI skill do?

A CI job fails on a named revision and the fix belongs in code, config or tests, not in the CI provider.

Why use Ci Fixer on TypingMind?

Because you install it once and use it with any model. Ci Fixer 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 Ci Fixer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hex/claude-council/tree/main/mods/council-pane/specialists/ci-fixer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ci Fixer?

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 Ci Fixer?

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

Is the Ci Fixer AI skill free?

Yes. It is published on GitHub by hex 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.

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