Front-End-Checklist

385 English rules across 11 categories, exposed as a website, an MCP server, and a plain README. Each rule page carries an explanation, remediation guidance, and verification steps.

Front-End Checklist describes itself as the open source front end quality system for humans and AI agents. It turns front end best practices into a practical review workflow you can browse on the web, run through MCP compatible tools, or work through directly in the README. The website is frontendchecklist.io, rules live at /rules, and an MCP server sits at mcp.frontendchecklist.io. A companion project, UX Patterns for Devs, helps you choose the right UI pattern before verifying implementation quality.

The numbers are stated up front: 385 English rules across 11 active categories, 11 MCP tools exposed by the hosted server, and rule pages with explanations, remediation guidance, and verification steps. The category list shows the spread: HTML with 25 rules, CSS with 32, JavaScript with 26, Performance with 43, Accessibility with 95, SEO with 94, Security with 22, Images with 25, Testing with 13, Privacy with 5, and Internationalization with 5.

Each rule carries a priority. Critical marks site breaking, compliance sensitive, or security sensitive issues that should be fixed first. High marks issues with major impact on user experience, accessibility, performance, or discoverability. Medium marks strong best practices that should be part of a normal front end quality review, and Low marks useful improvements that are situational or lower urgency. The legend appears before the rules so the meaning is clear from the start.

The MCP angle is well documented. You can connect an MCP capable agent for frontend code review across React, Next.js, HTML, CSS, JavaScript, accessibility, performance, SEO, security, images, privacy, i18n, and testing. Example uses include reviewing pasted code, auditing a live public URL, fetching a specific rule, and searching rules by keyword, category, or priority. A skills folder offers a global audit skill and rule specific skills like the https one, and contributing uses pnpm commands for validation, scoring, and regenerating artifacts.

• Source 1 · Project repository
• Source 2 · README