Frontend Code Review

OrganizationPopular

langgenius

frontend-code-review

Use only when the user explicitly requests a review or audit of frontend code under `web/` or `packages/dify-ui/`. Supports pending-change, file-focused, and pasted-diff reviews. Do not use for implementation-only requests, diagnosis without review intent, or backend-only code.

Overview

Publisher	langgenius
Repository	`dify`
Skill name	`frontend-code-review`
Stars	157.6K
Forks	24.9K
Bundled files	8
Links	Skill source Repository Homepage

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.
8 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by langgenius on GitHub. Read the source before you install it.

Installation

Install the Frontend Code Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/langgenius/dify/tree/main/.agents/skills/frontend-code-review
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.

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/langgenius/dify.git /tmp/dify
mkdir -p .claude/skills
cp -r /tmp/dify/.agents/skills/frontend-code-review .claude/skills/frontend-code-review

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Frontend Code Review 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 Code Review 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 Code Review 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 Code Review

Review the requested scope for concrete defects and violations of explicit project contracts. This skill owns review decisions; its references route to canonical rules without activating another skill's implementation workflow.

Evidence First

Establish the review scope from the requested files or current diff.
Read the changed lines, their behavior owner, and the nearest scoped AGENTS.md.
Trace public consumers, generated contracts, primitive APIs, or runtime configuration only when they decide correctness.
Report findings tied to an observable failure, violated contract, security boundary, or demonstrated maintenance risk. Explicit team conventions are contracts: establish their scope and exceptions, and do not invent user impact to justify a convention finding.

Rule Routing

Read only the packs matched by the diff:

DOM semantics, focus, keyboard, forms, disabled state, or visible interaction: references/accessibility-ui.md
Dify UI imports, Base UI wrappers, overlays, tokens, or primitive contracts: references/dify-ui.md
Component ownership, props, state, Effects, navigation, or module boundaries: references/component-architecture.md
Generated clients, Query, mutations, auth, SSR, URL state, or persistence: references/data-query-contracts.md
Test files or a concrete missing-regression-test finding: references/testing.md
Bundle, waterfall, rendering, or subscription cost supported by evidence: references/performance.md
Stable Dify runtime invariants in the named paths: references/dify-invariants.md
General TypeScript or styling quality not owned above: references/code-quality.md

Read packages/dify-ui/README.md, packages/dify-ui/AGENTS.md, packages/dify-ui/docs/overlays.md, or web/docs/test.md only when the reviewed code falls under that contract. Check current official documentation when local code and bundled references do not settle a framework, browser, or accessibility behavior.

Severity And Output

P0: security or privacy leak, data loss, production crash, or inaccessible critical workflow.
P1: user-visible regression, invalid API or authorization contract, hydration failure, or broken primary interaction.
P2: concrete maintainability, performance, test, or accessibility defect, or a material violation of an explicit project contract.
P3: minor actionable cleanup; omit unless the user requested a thorough audit.

Lead with findings ordered by severity. Include a tight file and line reference, the observed failure or applicable project rule, and a concrete fix direction. Explain the rule's applicability for convention findings; describe downstream consequences only when supported by evidence. When no findings remain, say so briefly and state any material verification gap. Do not add praise sections, speculative risks, or an unsolicited offer to implement fixes.

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 Code Review AI skill do?

Why use Frontend Code Review on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/langgenius/dify/tree/main/.agents/skills/frontend-code-review. 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 Code Review?

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 Code Review?

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

Is the Frontend Code Review AI skill free?

It is published on GitHub by langgenius. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Frontend Code Review

Evidence First

Rule Routing

Severity And Output

Bundled files

Frequently asked questions

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