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Hai Naming

Community
hylarucoder
hai-naming

Recommends names for concepts, identifiers, modules, files, entities, events, or product terms, or audits an existing naming set for misleading vocabulary and viewpoint drift. Use for “what should I call this?”, rename requests, or naming reviews(起名、命名、改名、名字不清楚). Give a concise answer for one local name; use the full vocabulary map and migration scope only for cross-module or public naming audits. Route boundary problems exposed by naming to hai-architecture.

Overview

Publisherhylarucoder
Repositoryhai-stack
Skill namehai-naming
Stars
284
Forks
15
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Hai Naming 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/hylarucoder/hai-stack.git /tmp/hai-stack
mkdir -p .claude/skills
cp -r /tmp/hai-stack/skills/hai-naming .claude/skills/hai-naming
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hai Naming 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 Hai Naming 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 Hai Naming 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.

Hai Naming

For Chinese readers, see SKILL.zh_CN.md. The English SKILL.md is the execution source of truth.

Purpose

Treat naming as a model of the system, not a thesaurus exercise. A useful name tells the intended reader what the concept is, who owns it, and how it differs from its neighbors without forcing them to reconstruct hidden context.

Choose the mode

  • Quick naming: one local variable, function, prop, file, or concept. Give three to five candidates, recommend one, and explain the decisive distinction briefly.
  • Naming audit: public or cross-module vocabulary, several related names, or a rename with migration impact. Build a vocabulary map, trace the call flow, and return prioritized renames.

Do not force an audit-sized reasoning trail onto a local identifier question.

Decision rules

  1. Name in context. Read the declaration, callers, neighboring concepts, layer, audience, and lifecycle available in the user's scope. Never invent a global model from one isolated snippet.
  2. Choose a viewpoint. Product names describe user intent, domain names describe durable concepts, runtime names describe execution responsibility, and adapter names describe the boundary crossed. Keep the viewpoint stable until a real boundary changes it.
  3. Preserve decisive information. Shorten only when the surrounding expression carries the omitted meaning. Public and cross-module names should usually be more explicit than local ones.
  4. Use one word per concept. The same concept keeps one term; different concepts do not share a convenient generic word.
  5. Name ownership, not incidental mechanics. Manager, Service, Helper, Data, Info, Context, get, and build are acceptable only when they accurately express the local model.
  6. Treat naming friction as evidence. If every candidate needs a paragraph of explanation, the concept may mix responsibilities or viewpoints. Recommend a design clarification instead of more synonyms.

Read references/principles.md when a public or cross-module decision needs the expanded context, call-flow, symmetry, lifecycle, or migration checks.

Workflow

Quick naming

  1. State the concept, reader, layer, and nearest competing term.
  2. Inspect the surrounding code or text the user supplied.
  3. Generate three to five candidates that differ meaningfully, not cosmetically.
  4. Recommend one and explain why the closest alternative loses.
  5. Flag a design problem only when the evidence actually makes naming unstable.

Naming audit

  1. Read the relevant declarations, callers, contracts, docs, and persisted/wire names.
  2. Map actors, concepts, lifecycle states, layer-specific vocabulary, and overloaded terms.
  3. Identify wrong viewpoint, lost information, stale vocabulary, collisions, and inconsistency.
  4. Prioritize public/API/domain names before small locals.
  5. For each rename, state old -> new, evidence, conceptual repair, affected surfaces, and whether compatibility is required by a real contract.
  6. Separate the recommended vocabulary from the migration plan.

Output

Use the matching mode in references/output-template.md. A quick answer should remain conversational and compact. An audit must include evidence and migration scope, but it does not need to expose a performative “top-of-head” reasoning chain. Explain only what changed after reading when that change affects the recommendation.

Use a different skill when

  • The name is awkward because module ownership or abstraction is wrong → hai-architecture.
  • The question is whether a field should exist or where it belongs → entity-model-auditor.
  • The user wants a bold direction change rather than a name → geju.
  • The scope is an entire React component API, not one identifier → react-component-diagnosis.

Not this skill

Do not act as a casing linter, rigid naming standard, or synonym generator. Project conventions constrain the answer, but conceptual clarity decides it.

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 Hai Naming AI skill do?

Recommends names for concepts, identifiers, modules, files, entities, events, or product terms, or audits an existing naming set for misleading vocabulary and viewpoint drift. Use for “what should I call this?”, rename requests, or naming reviews(起名、命名、改名、名字不清楚). Give a concise answer for one local name; use the full vocabulary map and migration scope only for cross-module or public naming audits. Route boundary problems exposed by naming to hai-architecture.

Why use Hai Naming on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hylarucoder/hai-stack/tree/main/skills/hai-naming. 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 Hai Naming?

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 Hai Naming?

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

Is the Hai Naming AI skill free?

It is published on GitHub by hylarucoder. 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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