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Code Structure

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michaelshimeles
code-structure

Use when multiple workflows duplicate the same operational logic, when deciding what belongs in actions vs shared services, or when refactoring repeated operational blocks across domain flows. Use when adding new features that share mechanics with existing ones.

Overview

Publishermichaelshimeles
Repositoryskills
Skill namecode-structure
Stars
1.2K
Forks
198
Bundled files
Instructions only
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 michaelshimeles on GitHub. Read the source before you install it.

Installation

Install the Code Structure 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/michaelshimeles/skills/tree/main/code-structure
  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/michaelshimeles/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/code-structure .claude/skills/code-structure
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Structure 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 Code Structure 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 Code Structure 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.

Service Layer Architecture

Overview

Two-layer separation: Actions orchestrate domain rules (the "why/when"), while a service layer centralizes reusable operational mechanics (the "how").

This prevents duplicated code, inconsistent behavior, and bugs fixed in one path but not others.

When to Use

  • Multiple callers need the same low-level operation (sandbox creation, email sending, payment processing)
  • You're copy-pasting operational logic between action files
  • A bug fix in one workflow doesn't propagate to others doing the same thing
  • Adding a new feature that shares mechanics with existing flows

Don't use when: Logic is truly domain-specific and used by only one caller.

Core Pattern

Orchestration Layer (Actions)          Service Layer (Shared Mechanics)
├── owns business rules                ├── owns reusable operations
├── owns state transitions             ├── owns provider/SDK interactions
├── owns auth/ownership checks         ├── owns command execution details
├── owns failure classification        ├── owns health checks / readiness
├── owns retries / user-facing errors  └── returns structured results
└── calls service functions

Rule of thumb:

  • "What this product flow means" → keep in actions
  • "How to do this operation reliably" → move to service layer

Quick Reference

Design PrincipleDoDon't
API shapeComposable capability blocksOne giant "do everything" method
Inputs/outputsExplicit params, structured returnsHidden global state, reaching into DB
MigrationExtract one block, replace one caller, verify, then migrate restRefactor everything at once
Domain logicKeep auth, policy, error classification in actionsLet service mutate domain state directly
Extraction triggerLogic repeated across 2+ callersLogic used once (over-abstraction)

Designing Service Functions

Design as capability blocks, not monoliths:

ts
// Good: composable, each caller chooses what to use
createManagedSandbox(...)
prepareRepo(...)
detectPackageManager(...)
installDependencies(...)
runBuildCommand(...)
startSandboxRuntime(...)

Each function should:

  • Accept all required data as explicit parameters
  • Return structured outputs (e.g., { ready, previewUrl, proxyPort })
  • Never reach into database/state directly
  • Make failure explicit (structured results, not swallowed errors)

This lets callers choose strict vs relaxed behavior per flow.

Migration Checklist

When extracting shared logic:

  1. Write the flow in action code first (clear behavior)
  2. Mark repeated operational chunks across callers
  3. Extract only repeated, non-domain chunks to service
  4. Replace one caller → verify → replace remaining callers
  5. Keep domain policy in actions (auth, status transitions, error classification)
  6. Run verification: typecheck, lint, confirm all flows still work

Anti-Patterns

Anti-PatternProblem
God serviceOne huge function hides all control flow
Leaky serviceService mutates database tables directly
Inconsistent APIEach function uses different argument styles and error semantics
Over-abstractionExtracting logic used by only one caller

Example: Email Service (Simple)

ts
// emailService.ts — shared mechanics
export async function sendWelcomeEmail(params: { to: string; name: string }) {
  const html = `<h1>Welcome ${params.name}</h1>`;
  await emailProvider.send(params.to, "Welcome", html);
}

// userSignup.ts — orchestration (owns WHEN to send)
if (user.marketingOptIn) {
  await sendWelcomeEmail({ to: user.email, name: user.name });
}

// adminInvite.ts — orchestration (different business rule, same mechanic)
await sendWelcomeEmail({ to: invitee.email, name: invitee.name });

Mental Model

New feature? → Write in action first → See repeated ops? → Extract to service
                                      → No repetition?  → Keep in action

Your architecture in one sentence: Actions orchestrate domain rules, while the service layer centralizes reusable operational mechanics with a composable, explicit-input API.

Frequently asked questions

What does the Code Structure AI skill do?

Use when multiple workflows duplicate the same operational logic, when deciding what belongs in actions vs shared services, or when refactoring repeated operational blocks across domain flows. Use when adding new features that share mechanics with existing ones.

Why use Code Structure on TypingMind?

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

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

Which AI models can use Code Structure?

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 Code Structure?

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

Is the Code Structure AI skill free?

It is published on GitHub by michaelshimeles. 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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