browser-audit

browser-audit is a skill for Codex from JohnWayneeee/ai-agent-skills. It costs 96 tokens per session (1,302 once invoked), scanned A, original, MIT.

A browser-based check of a live, preview, or local web page for accessibility, search-engine setup, speed, and common user-experience problems.

In plain words
What is it for?
Use it before deployment to review WCAG 2.2 AA concerns, Lighthouse results, browser errors, page structure, forms, navigation, and focus behavior.
Why use it?
It finds issues that may be missed during development, such as poor keyboard support, missing labels, weak contrast, broken links, or missing page metadata.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it before deployment to review WCAG 2.2 AA concerns, Lighthouse results…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/johnwayneeee/ai-agent-skills/browser-audit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add JohnWayneeee/ai-agent-skills --skill browser-audit
Clone the repo
git clone --depth 1 https://github.com/JohnWayneeee/ai-agent-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for browser-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/johnwayneeee/ai-agent-skills/browser-audit.svg)](https://agentmods.dev/skills/johnwayneeee/ai-agent-skills/browser-audit)
Your own site
<a href="https://agentmods.dev/skills/johnwayneeee/ai-agent-skills/browser-audit"><img src="https://agentmods.dev/badge/skills/johnwayneeee/ai-agent-skills/browser-audit.svg" alt="Measured on agentmods" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,302 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.01302
Opus 5 $0.00048 $0.00651
Sonnet 5 $0.00019 $0.00260
Haiku 4.5 $0.00010 $0.00130

Measured 6d ago against content hash 8c6050d24333, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

browser-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/browser-audit/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Browser Audit

Audit the rendered page in a real browser before deployment. Treat Lighthouse and automated accessibility checks as strong signals, not as a complete conformance claim. Always include manual browser checks for anything automation cannot prove reliably.

Workflow

  1. Confirm scope: target URL, viewport(s), auth state, and key user flows. If unspecified, audit the provided/current page at desktop and mobile widths.
  2. Open the page in a browser. For localhost or preview URLs, use the available browser automation/in-app browser tooling. Capture at least one screenshot per viewport when possible.
  3. Run automated checks:
    • Lighthouse categories: accessibility, seo, best-practices, and performance when performance risk matters.
    • Browser console errors, failed network requests, mixed content, CSP/security warnings.
    • DOM checks for title, meta description, canonical, robots, viewport, html[lang], heading structure, image alt text, form labels, accessible names, duplicate IDs, invalid/broken ARIA references, landmark presence, and empty/ambiguous links/buttons.
    • Accessibility tree inspection for key navigation, dialogs, controls, forms, and repeated components.
  4. Run manual browser checks:
    • Keyboard-only navigation: Tab, Shift+Tab, Enter, Space, Escape, arrow keys for composite widgets, no unreachable controls, no unexpected traps.
    • Focus visibility and focus management: visible focus, not obscured by sticky UI, dialogs trap/restore focus, route changes place focus sensibly.
    • Contrast and visual states: text, icons, borders, disabled/error/focus states, hover-only information, active navigation.
    • Responsive UX: mobile width, 200% zoom if practical, target sizes, no horizontal scroll, no overlapping text or controls.
    • Forms and validation: labels, required/invalid states, error messages, autocomplete, redundant-entry risk, submit feedback.
    • Critical UX: broken layouts, blocked primary CTA, loading states that never resolve, overlays hiding content, privacy/cookie banners blocking keyboard users.
  5. Map findings to severity and priority. Do not report issues from static source inspection alone unless they are confirmed in the rendered browser or clearly marked as source-only.
  6. Produce the structured report in the format below. Explicitly mark manual checks that could not be completed.

Read the full file on GitHub · 106 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 106 lines · 96 tokens per session scan A 8c6050d24333

Subscribe to this mod's changes

browser-audit is a skill published in the GitHub repository JohnWayneeee/ai-agent-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 96 tokens to every session and 1,302 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

browser-subagent-task-bounding

How to constrain browser subagents with deterministic stop conditions, step ceilings (max 5-8 steps), and selector-targeted DOM extraction to prevent runaway token costs and infinite navigation loops.

alivirgo/Major-AI-Skills · 44 tokens

awt-e2e-testing

AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g.

sickn33/agentic-awesome-skills · 74 tokens

facebook-page-profile-posts

Scrapes posts from any public Facebook Page or personal Profile timeline, returning structured data including post text, author info with profile picture, engagement metrics (likes/comments/shares), full reaction breakdown (Like/Love/Wow/Haha/Sad/Angry/Care as both array and flat counts), hashtags and external links…

browser-act/skills · 181 tokens

amazon-bestseller-listing

Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and…

browser-act/skills · 300 tokens

amazon-search-listing

Amazon search and category listing scraper: extract product listings from any Amazon search results page, keyword search URL, or category browse page and return per-item cards (asin, title, url, image, price, listPrice, stars, reviewCount, badges, isAmazonChoice, isBestSeller, isSponsored, delivery, boughtInPast…

browser-act/skills · 341 tokens

etsy-product-detail

Etsy product detail scraper: given an Etsy listing URL, returns full product detail including listingId, title, priceCurrent, priceOriginal, currency, images (all), description, shopName, shopUrl, rating, reviewCount, favorites, inCartCount, variations (with per-option price ranges), highlights, listedDate…

browser-act/skills · 187 tokens