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Frontend Style Orchestrator

Community
citizenll
frontend-style-orchestrator

Transform user-provided visual style prompts into frontend webpage design or redesign implementations through a repeatable pipeline (style extraction, design contract, token system, implementation, and QA). Use when the user asks to build a web page in a specific style, refactor an existing page to a new style, or iterate through multiple style directions across rounds.

Overview

Publishercitizenll
Repositoryfrontend-style-orchestrator
Skill namefrontend-style-orchestrator
Stars
7
Forks
0
Bundled files
16
Links
Skill sourceRepository
  • 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.

  • 16 bundled files

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

  • Open source

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

Installation

Install the Frontend Style Orchestrator 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/citizenll/frontend-style-orchestrator/tree/main
  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/citizenll/frontend-style-orchestrator.git \
  .claude/skills/frontend-style-orchestrator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Frontend Style Orchestrator 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 Frontend Style Orchestrator 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 Frontend Style Orchestrator 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.

Frontend Style Orchestrator

Deliver consistent, high-quality frontend styling outcomes from free-form style prompts.

Use This Execution Model

  1. Read the user prompt and classify the task mode:
    • build-new: create a new page/component with the requested style.
    • restyle-existing: keep existing structure/business logic and replace visual language.
  2. Resolve hard constraints first:
    • Stack and framework.
    • Files that can or cannot be changed.
    • Responsiveness, accessibility, performance constraints.
  3. Convert the style prompt into a compact design contract:
    • Mood and tone.
    • Color system.
    • Typography direction.
    • Layout rhythm.
    • Component treatment.
    • Motion behavior.
  4. Select a style pack:
    • If a matching pack exists in references/style-packs/, adapt it.
    • Otherwise create a new pack using scripts/new_style_pack.ps1 and fill it.
  5. Implement with token-first architecture:
    • Define CSS variables/tokens before component-level styling.
    • Separate structure from skin (layout classes vs style classes).
    • Keep visual decisions centralized for easy iteration.
  6. Validate against quality gates in references/quality-gates.md.
  7. Return concise delivery notes:
    • What changed.
    • Which files were modified.
    • Any tradeoffs or remaining risks.

Reference Loading Rules

  • Read references/workflow.md for end-to-end execution order.
  • Read references/style-pack-schema.md when creating or updating a style pack.
  • Read references/quality-gates.md before finalizing changes.
  • Read only the specific file in references/style-packs/ that matches the target style.

Output Contract Per Request

For each style request, produce:

  1. Style Contract (short): 5-8 bullets describing core visual intent.
  2. Implementation (code changes): update or create frontend files.
  3. Verification (short): report responsiveness/accessibility checks completed.

Iteration Rules

  • Keep semantic HTML and behavior intact unless user explicitly asks for structural rewrite.
  • Prefer incremental edits for restyling tasks; avoid unnecessary refactors.
  • When user sends a new style prompt, create a new style pack or revise an existing one, then re-run the same pipeline.

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 Frontend Style Orchestrator AI skill do?

Transform user-provided visual style prompts into frontend webpage design or redesign implementations through a repeatable pipeline (style extraction, design contract, token system, implementation, and QA). Use when the user asks to build a web page in a specific style, refactor an existing page to a new style, or iterate through multiple style directions across rounds.

Why use Frontend Style Orchestrator on TypingMind?

Because you install it once and use it with any model. Frontend Style Orchestrator 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 Frontend Style Orchestrator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/citizenll/frontend-style-orchestrator/tree/main. 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 Frontend Style Orchestrator?

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 Frontend Style Orchestrator?

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

Is the Frontend Style Orchestrator AI skill free?

It is published on GitHub by citizenll. 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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