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Typescript

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tuanductran
typescript

Repository guidance for writing, reviewing, and maintaining TypeScript code within the hr-skills monorepo. Covers project conventions, compiler settings, module structure, and development workflows.

Overview

Publishertuanductran
Repositoryhr-skills
Skill nametypescript
Stars
78
Forks
20
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 tuanductran on GitHub. Read the source before you install it.

Installation

Install the Typescript 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/tuanductran/hr-skills/tree/main/.agents/skills/typescript
  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/tuanductran/hr-skills.git /tmp/hr-skills
mkdir -p .claude/skills
cp -r /tmp/hr-skills/.agents/skills/typescript .claude/skills/typescript
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Typescript 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 Typescript 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 Typescript 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.

TypeScript

This skill describes how TypeScript is used throughout the hr-skills monorepo. It covers repository conventions, compiler configuration, module organization, type safety, and development workflows.

The repository uses modern TypeScript with strict compiler settings, ECMAScript modules, and Bun as the runtime.

Supported tasks

  • Explain TypeScript conventions used by this repository
  • Review TypeScript code for correctness and maintainability
  • Improve type safety without changing runtime behavior
  • Recommend repository-consistent TypeScript patterns
  • Organize modules and exports
  • Review public APIs
  • Validate compiler configuration
  • Explain workspace TypeScript structure
  • Troubleshoot common TypeScript errors

Repository conventions

This repository follows several core principles.

  • Prefer strict type safety.
  • Prefer explicit public APIs.
  • Keep modules focused on a single responsibility.
  • Use ECMAScript modules exclusively.
  • Prefer native language features over unnecessary abstractions.
  • Avoid runtime dependencies when the type system is sufficient.

Compiler configuration

The repository enables modern TypeScript features including:

  • strict
  • moduleResolution: bundler
  • module: Preserve
  • target: ESNext
  • noEmit
  • isolatedModules
  • verbatimModuleSyntax
  • exactOptionalPropertyTypes
  • noUncheckedIndexedAccess
  • noImplicitReturns
  • noImplicitOverride
  • useUnknownInCatchVariables

These settings prioritize correctness, maintainability, and predictable builds.

Project structure

Workspace packages typically organize source code as:

text
src/
test/
tsconfig.json

Packages extend the shared repository TypeScript configuration while keeping package-specific configuration minimal.

Code organization

Prefer small, focused modules.

  • One responsibility per file.
  • Export only public APIs.
  • Keep helper functions private unless reused.
  • Avoid circular dependencies.
  • Group related types with their implementation.

Type design

Prefer expressive types over assertions.

Recommended patterns include:

  • discriminated unions
  • generic functions
  • utility types
  • readonly objects
  • literal types
  • as const where appropriate

Avoid:

  • unnecessary any
  • excessive type assertions
  • duplicated type definitions
  • overly complex conditional types

Imports and exports

  • Prefer named exports.
  • Keep imports grouped and organized.
  • Import only what is required.
  • Use relative imports within a package.
  • Use workspace:* dependencies for internal packages.

Common commands

Run TypeScript type checking.

bash
bun run typecheck

Run all repository tests.

bash
bun run test

Build every workspace package.

bash
bun run build

Key prompts

Type safety

  • "Review this TypeScript code for type safety."
  • "Explain this compiler error."
  • "Reduce unnecessary type assertions."
  • "Improve the inferred types."

Repository conventions

  • "Rewrite this file following repository conventions."
  • "Review the module organization."
  • "Recommend a cleaner public API."
  • "Validate this package structure."

Configuration philosophy

Repository configuration should remain as simple as possible.

  • Prefer tool defaults over explicit configuration.
  • Extend shared repository configuration instead of duplicating settings.
  • Add package-specific configuration only when the defaults are insufficient.
  • Keep build and compiler configuration easy to understand and maintain.

Refactoring

  • "Simplify this TypeScript implementation."
  • "Extract reusable utilities."
  • "Remove duplicated types."
  • "Improve module boundaries."

Development

  • "Explain this tsconfig option."
  • "Generate a repository-compatible tsconfig."
  • "Recommend TypeScript best practices for this package."
  • "Review this pull request for TypeScript issues."

Examples

Run repository type checking.

bash
bun run typecheck

Package tsconfig.json files extend the shared repository configuration and include only the package sources.

json
{
  "extends": "../../tsconfig.json",
  "include": ["src", "test"]
}

Tips

  • Prefer inference when it improves readability.
  • Add explicit types to exported APIs.
  • Keep implementations simpler than their type definitions.
  • Use unknown instead of any whenever possible.
  • Validate changes with bun run typecheck.
  • Keep package-specific TypeScript configuration minimal and rely on shared defaults whenever possible.

Common issues

  • Exporting implementation details unnecessarily.
  • Using any where stronger types are possible.
  • Duplicating types across packages.
  • Mixing runtime logic with type definitions.
  • Ignoring compiler diagnostics.
  • Creating modules with multiple unrelated responsibilities.

Best practices

  • Keep public APIs stable.
  • Prefer composition over inheritance.
  • Write reusable utility types only when they improve clarity.
  • Use strict compiler settings consistently.
  • Review exported types as carefully as runtime code.
  • Keep TypeScript code easy to understand before optimizing for brevity.

Frequently asked questions

What does the Typescript AI skill do?

Repository guidance for writing, reviewing, and maintaining TypeScript code within the hr-skills monorepo. Covers project conventions, compiler settings, module structure, and development workflows.

Why use Typescript on TypingMind?

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

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

Which AI models can use Typescript?

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 Typescript?

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

Is the Typescript AI skill free?

Yes. It is published on GitHub by tuanductran 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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