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Minimal Code Discipline

CommunityPopular
Yeachan-Heo
minimal-code-discipline

YAGNI-ladder coding discipline for writing changes — existence-first, reuse before writing, dependency ladder, shortest correct diff, with non-negotiables that must never be minimized away

Overview

PublisherYeachan-Heo
Repositoryoh-my-claudecode
Skill nameminimal-code-discipline
Stars
39.2K
Forks
3.5K
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 Yeachan-Heo on GitHub. Read the source before you install it.

Installation

Install the Minimal Code Discipline 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.
  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/Yeachan-Heo/oh-my-claudecode.git /tmp/oh-my-claudecode
mkdir -p .claude/skills
cp -r /tmp/oh-my-claudecode/skills/minimal-code-discipline .claude/skills/minimal-code-discipline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Minimal Code Discipline 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 Minimal Code Discipline 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 Minimal Code Discipline 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.

Minimal Code Discipline

Use this skill to apply a minimal-code (YAGNI-ladder) discipline while planning and writing code changes. It keeps diffs small and obviously correct without sacrificing the checks that keep users safe.

This skill complements ai-slop-cleaner: that skill cleans slop after it lands; this one keeps it from being written.

When to Use

Use this skill when:

  • the user asks for a minimal, lean, YAGNI, or smallest-possible-diff implementation
  • a plan or in-flight change is growing beyond the stated request
  • writing new code where scope creep, reinvented helpers, or speculative generality are likely
  • reviewing a proposed diff for size before implementation

When Not to Use

Do not use this skill when:

  • the user explicitly asks for a broad, feature-rich, or future-proofed build (their explicit scope wins)
  • the task is exploratory scaffolding the user has marked as throwaway
  • minimization pressure would touch protected behavior (see Non-Negotiables)

The Discipline

Existence first. Ask whether the change needs to exist at all; skip work that serves only a speculative future need.

Reuse before writing. Search the codebase for an existing helper, type, or pattern before writing anything new. Never copy a helper that already lives a few files away — reuse it or extract it to one shared location.

Dependency ladder. Reach for the standard library first, then platform-native capability, then an already-installed dependency. Hand-written code is the last resort. Do not introduce a new dependency when a few lines of code suffice, unless the user explicitly requested or approved it.

Understand before minimizing. Read the affected code and follow its execution path first. Ship the shortest correct diff once the problem is understood — code you never write never breaks.

Boring over clever. Prefer boring, obviously-correct code over clever code.

Mark the ceiling. Record deliberate simplifications with a short comment naming the accepted limit and what would justify replacing it.

Root cause, not symptoms. Fix bugs at the root cause shared by every caller, not with a separate patch for each reported symptom.

Non-Negotiables

Never minimize away:

  • validation wherever a trust boundary is crossed
  • error handling that guards against data loss
  • security controls
  • accessibility fundamentals
  • scope the user explicitly requested

Verification

Before reporting completion, confirm:

  • every added line earns its place (no speculative generality, no duplicate helpers)
  • the diff is the shortest one that correctly solves the stated problem
  • non-negotiables are intact
  • tests still pass and behavior is unchanged except as requested

Frequently asked questions

What does the Minimal Code Discipline AI skill do?

YAGNI-ladder coding discipline for writing changes — existence-first, reuse before writing, dependency ladder, shortest correct diff, with non-negotiables that must never be minimized away

Why use Minimal Code Discipline on TypingMind?

Because you install it once and use it with any model. Minimal Code Discipline 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 Minimal Code Discipline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/minimal-code-discipline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Minimal Code Discipline?

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 Minimal Code Discipline?

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

Is the Minimal Code Discipline AI skill free?

Yes. It is published on GitHub by Yeachan-Heo 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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