frontend-code-review — for Claude Code frontend-code-review, official, for Claude Code, ide skills, agentic-ai, agentic-framework, agentic-workflow, gemini, low-code, nextjs

Verified
v1.0.0

About this Skill

Ideal for AI agents that need frontend code review. frontend-code-review is an AI agent skill for frontend code review.

Features

Frontend Code Review
File-targeted review – review the specific file(s) the user names and report the relevant
Stick to the checklist below for every applicable file and mode.
Flag each rule violation with urgency metadata so future reviewers can prioritize fixes.
For each rule in the review point, note where the code deviates and capture a representative

# Core Topics

langgenius langgenius
[139.2k]
[21822]
Updated: 4/26/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reviewed Landing Page Review Score: 11/11

Killer-Skills keeps this page indexable because it adds recommendation, limitations, and review signals beyond the upstream repository text.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review Locale and body language aligned
Review Score
11/11
Quality Score
78
Canonical Locale
en
Detected Body Locale
en

Ideal for AI agents that need frontend code review. frontend-code-review is an AI agent skill for frontend code review.

Core Value

frontend-code-review helps agents frontend code review. Trigger when the user requests a review of frontend files (e.g., .tsx, .ts, .js). This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Ideal Agent Persona

Ideal for AI agents that need frontend code review.

Capabilities Granted for frontend-code-review

Applying Frontend Code Review
Applying File-targeted review – review the specific file(s) the user names and report the relevant
Applying Stick to the checklist below for every applicable file and mode

! Prerequisites & Limits

  • When invoked, the response must exactly follow one of the two templates:
  • Found <N urgent issues need to be fixed:
  • Don't compress the blank lines between sections; keep them as-is for readability.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Curated Collection Review

Reviewed In Curated Collections

This section shows how Killer-Skills includes, reviews, and maintains this skill inside curated collections, so you can see where it fits in practical selection paths instead of relying only on the upstream README.

Reviewed Collection

OpenAI Workflow Tools for Prompt, Eval, and Agent Teams

Reviewed 2026-04-17

Reviewed on 2026-04-17 for setup clarity, eval usefulness, runtime visibility, and maintainer reliability. We kept the tools that help OpenAI teams move from experiments to repeatable production routines.

OpenAI visitors usually arrive with a concrete job: improve prompts, add evals, debug runtime behavior, or make agent operations easier to hand off. This page narrows the shortlist around those jobs.

12 entries Killer-Skills curation review with monthly collection checks.
Reviewed Collection

Next.js Workflow Tools to Install First

Reviewed 2026-04-17

Reviewed on 2026-04-17 against Next.js workflow fit, installation clarity, team adoption, and full-stack delivery usefulness. This page is now positioned as an installation-focused Next.js entry point instead of a broad framework roundup.

We prioritize this page because Next.js-intent users usually need a shortlist they can install, validate, and carry into real full-stack release loops quickly.

12 entries Maintained through Killer-Skills curation review with trust, install-path, and setup checks.
Reviewed Collection

Python Workflow Tools to Install First

Reviewed 2026-04-17

Reviewed on 2026-04-17 against Python workflow fit, installation clarity, team adoption, and day-to-day engineering usefulness. This page is now positioned as an installation-focused Python entry point instead of a broad language roundup.

We prioritize this page because Python-intent users usually need a shortlist they can install, validate, and carry into real automation and delivery loops quickly.

12 entries Maintained through Killer-Skills curation review with install, documentation, and Python workflow checks.
After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is frontend-code-review?

Ideal for AI agents that need frontend code review. frontend-code-review is an AI agent skill for frontend code review.

How do I install frontend-code-review?

Run the command: npx killer-skills add langgenius/dify/frontend-code-review. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for frontend-code-review?

Key use cases include: Applying Frontend Code Review, Applying File-targeted review – review the specific file(s) the user names and report the relevant, Applying Stick to the checklist below for every applicable file and mode.

Which IDEs are compatible with frontend-code-review?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for frontend-code-review?

When invoked, the response must exactly follow one of the two templates:. Found <N urgent issues need to be fixed:. Don't compress the blank lines between sections; keep them as-is for readability..

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add langgenius/dify/frontend-code-review. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use frontend-code-review immediately in the current project.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

frontend-code-review

Install frontend-code-review, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Frontend Code Review

Intent

Use this skill whenever the user asks to review frontend code (especially .tsx, .ts, or .js files). Support two review modes:

  1. Pending-change review – inspect staged/working-tree files slated for commit and flag checklist violations before submission.
  2. File-targeted review – review the specific file(s) the user names and report the relevant checklist findings.

Stick to the checklist below for every applicable file and mode.

Checklist

See references/code-quality.md, references/performance.md, references/business-logic.md for the living checklist split by category—treat it as the canonical set of rules to follow.

Flag each rule violation with urgency metadata so future reviewers can prioritize fixes.

Review Process

  1. Open the relevant component/module. Gather lines that relate to class names, React Flow hooks, prop memoization, and styling.
  2. For each rule in the review point, note where the code deviates and capture a representative snippet.
  3. Compose the review section per the template below. Group violations first by Urgent flag, then by category order (Code Quality, Performance, Business Logic).

Required output

When invoked, the response must exactly follow one of the two templates:

Template A (any findings)

# Code review
Found <N> urgent issues need to be fixed:

## 1 <brief description of bug>
FilePath: <path> line <line>
<relevant code snippet or pointer>


### Suggested fix
<brief description of suggested fix>

---
... (repeat for each urgent issue) ...

Found <M> suggestions for improvement:

## 1 <brief description of suggestion>
FilePath: <path> line <line>
<relevant code snippet or pointer>


### Suggested fix
<brief description of suggested fix>

---

... (repeat for each suggestion) ...

If there are no urgent issues, omit that section. If there are no suggestions, omit that section.

If the issue number is more than 10, summarize as "10+ urgent issues" or "10+ suggestions" and just output the first 10 issues.

Don't compress the blank lines between sections; keep them as-is for readability.

If you use Template A (i.e., there are issues to fix) and at least one issue requires code changes, append a brief follow-up question after the structured output asking whether the user wants you to apply the suggested fix(es). For example: "Would you like me to use the Suggested fix section to address these issues?"

Template B (no issues)

## Code review
No issues found.

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