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Maintain Like Corbin

Community
crutchcorn
maintain-like-corbin

Resolve maintenance problems using Corbin Crutchley's preferences. Use when fixing test, type, or tooling failures, investigating dependency-owned bugs, completing migration cleanup, or documenting environment configuration. Fix underlying causes and keep cleanup scoped; do not audit or refactor unrelated code by default.

Overview

Publishercrutchcorn
Repositoryskills
Skill namemaintain-like-corbin
Stars
56
Forks
0
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by crutchcorn on GitHub. Read the source before you install it.

Installation

Install the Maintain Like Corbin 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/crutchcorn/skills/tree/main/maintain-like-corbin
  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/crutchcorn/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/maintain-like-corbin .claude/skills/maintain-like-corbin
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Maintain Like Corbin 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 Maintain Like Corbin 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 Maintain Like Corbin 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.

Maintain Like Corbin

Leave the affected system easier to maintain by fixing the cause and completing the requested change. Preserve unrelated work and avoid expanding a focused repair into a general cleanup.

Fix the cause of a failure

Understand what the failing check or broken behavior is demonstrating before changing code or configuration. Correct the underlying problem rather than silencing the signal.

  • Do not disable a check, skip a failing test, weaken an assertion, add a broad suppression, or cast away a type error merely to make the task appear complete.
  • A check or configuration can itself be wrong. When evidence identifies that as the cause, correct it while retaining coverage of the intended invariant; explain why the old check was inaccurate.
  • Keep type and tooling repairs separate from unrelated runtime behavior. Do not change application semantics to satisfy a compiler or linter unless the diagnostic exposes a real runtime defect that is part of the task.
  • Prefer the smallest repair that restores the intended contract. Run the relevant existing checks and verify the behavior that motivated the fix.

When adding tests, prefer explicit, readable cases over loops that hide distinct scenarios, setup, or assertions. Preserve useful existing data-driven coverage unless changing it serves the requested work; do not rewrite tests solely to impose a preferred style.

Investigate dependency-owned bugs

When the evidence points to a dependency, isolate the failing behavior and inspect the relevant upstream source, issue history, and releases. Check current primary sources for an existing fix or supported workaround before adding a local patch.

Prefer a compatible upstream fix when it resolves the problem within scope. If a local workaround is necessary, keep it narrow, explain the dependency defect and the condition for removing the workaround, and add meaningful regression coverage when warranted. Avoid broad upgrades or dependency replacement unless the task requires them.

Investigating upstream is not permission to publish an issue, comment, pull request, or other message. Prepare a useful reproduction or proposed fix locally when helpful; publish only when the user authorizes that external action. Do not keep retrying a failed external mutation without understanding its outcome.

Finish migrations within their scope

For vanilla JavaScript-to-framework UI migrations, check whether the old controller, event bus, or subscription layer still exists only to trigger framework renders. Move that application-owned state into framework primitives and expose values/actions directly; a hook around the unchanged controller is not a completed ownership migration. Preserve shared lifetime and actual persistence, retry, ordering, and conflict behavior. Keep adapters for genuinely external owners. If architect-like-corbin is available, its framework-state migration reference provides a worked example.

After the replacement works, remove code, dependencies, configuration, scripts, and documentation made obsolete by that migration. Check actual references and consumers before removal; a name that looks old is not proof that it is unused.

For JavaScript/TypeScript projects, use Knip to identify unused code and dependencies. Check its configured entrypoints and dynamic consumers before acting on a finding; static analysis is evidence to investigate, not automatic permission to delete every reported item.

Update affected imports, package manifests and lockfiles, commands, and configuration examples together. Preserve compatibility or rollback paths that remain part of the requirements. Run the relevant build, type, lint, and behavior checks to confirm the migration no longer depends on the removed pieces. Do not treat this as authorization to clean up unrelated parts of the repository.

Document configuration without exposing secrets

Use .env.example to document the configuration the affected application needs. Include variable names, required versus optional status, useful setup context, and safe defaults or obvious placeholders. Keep the example aligned with actual configuration consumers.

Actual secrets must never enter agent context, tool output, generated examples, or responses. Inspect .env.example, configuration schemas, and source references for the necessary names rather than opening secret-bearing environment files or dumping process environments. Do not request that the user paste a secret into chat.

When a command needs existing credentials, let the established runtime or credential mechanism supply them without reading or echoing their values. Avoid tracing or debug output that could reveal them. If a value is missing, tell the user its exact name and the specific place to set it, such as the application's local .env file or the shell profile the project documents, and use sanitized errors and presence checks that do not print values.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Maintain Like Corbin AI skill do?

Resolve maintenance problems using Corbin Crutchley's preferences. Use when fixing test, type, or tooling failures, investigating dependency-owned bugs, completing migration cleanup, or documenting environment configuration. Fix underlying causes and keep cleanup scoped; do not audit or refactor unrelated code by default.

Why use Maintain Like Corbin on TypingMind?

Because you install it once and use it with any model. Maintain Like Corbin 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 Maintain Like Corbin in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/crutchcorn/skills/tree/main/maintain-like-corbin. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Maintain Like Corbin?

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 Maintain Like Corbin?

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

Is the Maintain Like Corbin AI skill free?

It is published on GitHub by crutchcorn. Check the repository for licensing terms. 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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