agent-web-auditlisted

Audit a website or web app for AI-agent readiness, accessibility, and AI-search legibility, then fix the issues found. Use this skill whenever the user wants their site to work well for AI agents or LLMs (Claude, ChatGPT, Perplexity, Grok, Gemini, browser agents), or mentions "agentic SEO", "GEO", "AEO", "AI-friendly site", "agent-ready", "accessibility tree", "llms.txt", "make my site readable for AI", or the Lighthouse "Agentic Browsing" audit. Also trigger when the user asks to check or fix a frontend for semantic HTML, ARIA, label linking, cursor:pointer, layout stability, or how a site appears to crawlers and agents. Works on plain HTML, React/Next.js, Vue, and server-rendered templates. Trigger even if the user only says "make this site useful for AI" without naming a specific check.
ahmadabdulnasir/agent-ai-readiness · ★ 0 · Web & Frontend · score 72

Install: claude install-skill ahmadabdulnasir/agent-ai-readiness

# Agent web audit This skill audits a web project for how well AI agents and LLMs can read, navigate, and act on it, then applies the fixes. It covers three overlapping concerns that share one root cause: 1. Agent readiness: can an autonomous agent perceive and operate the interface (screenshots, DOM, accessibility tree). 2. Accessibility: the same signals a screen reader needs. Agent-readiness is accessibility restated for a new visitor class, so fixing one fixes both. 3. AI-search legibility: can crawlers reach the content and is it worth citing (GEO/AEO). The standard this is built on is Google's web.dev "Build agent-friendly websites" guidance (April 2026), the Lighthouse 13.3 "Agentic Browsing" audit (May 2026), and Google's Search Central generative-AI optimization guide (May 2026). The whole point: there is no separate AI layer. Clean, semantic, accessible, crawlable HTML is the entire game. ## What this skill does Given a web project (whole repo by default, or a folder/file if the user points at one): 1. Size up: detect the stack (plain HTML, React, Next.js, Vue, server templates) and whether Tailwind is in use, since one of the highest-hit issues is Tailwind-version-specific. 2. Scan: run `scripts/scan.sh` to grep for the common machine-readability problems across the whole project. 3. Deep read: open the files the scan flags and confirm each finding against `references/agent-rules.md`. 4. Report: write a findings report grouped by impact, with file:line refere