agent-lighthouse
Health Pass
- License — License: Apache-2.0
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 11 GitHub stars
Code Warn
- fs module — File system access in action.yml
Permissions Pass
- Permissions — No dangerous permissions requested
No AI report is available for this listing yet.
Lighthouse-style audits for AI-agent readiness, LLM crawlers, MCP clients, and the agentic web
🗼 Agent Lighthouse
Lighthouse, but for AI agents.
Audit whether ChatGPT, Claude, Perplexity, MCP clients, AI crawlers, and agentic browsers can discover, parse, cite, and act on your website.
⚡ Quickstart
Run a zero-install scan directly in your terminal. The --view flag opens the standalone HTML report for screenshots, stakeholder review, and pull-request artifacts.
# Instant audit (prints terminal report & generates HTML + JSON reports)
npx @forkpoint/agent-lighthouse https://yourstore.com
# Open the standalone HTML report in your browser
npx @forkpoint/agent-lighthouse https://yourstore.com --view
# Run in CI and fail if score is below threshold
npx @forkpoint/agent-lighthouse https://staging.yourstore.com --min-score 85
Agent Lighthouse checks 207 rules covering llms.txt, robots.txt crawler policy, Schema.org, OpenAPI discovery, WebMCP action surfaces, AEO/GEO content structure, accessibility, and technical readiness.
🎯 What Agent Lighthouse Checks
Agent Lighthouse evaluates websites across 10 audit categories grouped into 3 readiness pillars:
├── 1. Agentic Readiness
│ ├── AI Agent Tools & Action Surfaces (WebMCP manifests, OpenAPI specs, agents.json, ai-plugin.json)
│ ├── Content Discoverability (llms.txt, llms-full.txt, sitemaps, commerce links)
│ └── AI Crawler Permissions (robots.txt rules for GPTBot, ClaudeBot, PerplexityBot, etc.)
│
├── 2. AI Search Optimization
│ ├── Answer Engine Optimization (AEO) (direct answerability, step lists, table schemas)
│ └── Generative Engine Optimization (GEO) (unique data density, authoritative citations)
│
└── 3. Technical Foundation
├── Structured Data & Schema Markup (Schema.org Product, Offer, SKU, GTIN, Organization)
├── Meta Tags & AI Head Elements (AI content declarations, canonicals, Open Graph)
├── Semantic HTML & Content Structure (Headings hierarchy, landmarks, semantic tags)
├── Accessibility & Agent Interaction (Form labels, button roles, interactable elements)
└── Technical Readiness & Security (HTTPS, security.txt, TTFB response latency)
📦 Packages & Architecture
This repository is organized as a lightweight pnpm monorepo published under the @forkpoint scope:
| Package | npm Package | Description |
|---|---|---|
packages/cli |
@forkpoint/agent-lighthouse |
Main CLI binary (npx @forkpoint/agent-lighthouse <url>). |
packages/core |
@forkpoint/agent-lighthouse-core |
Core gatherer-audit engine, scoring algorithms, and types. |
packages/report |
@forkpoint/agent-lighthouse-report |
Standalone HTML, Markdown, and unified report view-model. |
packages/mcp |
@forkpoint/agent-lighthouse-mcp |
Model Context Protocol (MCP) server for Claude / Cursor / IDEs. |
🛡️ GitHub Actions CI
Use Agent Lighthouse as a pull-request gate for agentic readiness regressions:
name: Agent Lighthouse
on:
pull_request:
branches: [main]
jobs:
agent-lighthouse:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ForkPoint/agent-lighthouse@main
with:
url: https://staging.yourstore.com
preset: ecommerce
min-score: "85"
github-token: ${{ secrets.GITHUB_TOKEN }}
The action generates terminal, HTML, JSON, and Markdown reports. Set comment-on-pr: true with github-token to post the Markdown summary on pull requests. See the marketplace setup guide for release-ready examples.
💻 Programmatic Node.js / TypeScript SDK
import { runScan } from "@forkpoint/agent-lighthouse-core";
import {
buildReportView,
generateHtmlReport,
} from "@forkpoint/agent-lighthouse-report";
const report = await runScan("https://example.com");
const view = buildReportView(report);
console.log(`Overall Score: ${view.overallScore}/100 (${view.scoreTier})`);
// Generate standalone HTML report
const html = generateHtmlReport(report);
🤖 Model Context Protocol (MCP) Server
Add Agent Lighthouse to your Claude Desktop or Cursor IDE to let AI coding agents audit live staging URLs:
{
"mcpServers": {
"agent-lighthouse": {
"command": "npx",
"args": ["-y", "@forkpoint/agent-lighthouse-mcp"]
}
}
}
📣 Share Your Score
Generated reports are standalone files, so teams can attach them to pull requests, send them to clients, or publish before/after improvements.
[](https://github.com/ForkPoint/agent-lighthouse)
If you run Agent Lighthouse on a public site, share the result through the site score template. Good examples help other developers learn what agent-ready sites look like.
More launch material lives in:
- Promotion kit
- Benchmark report
- Badge generator notes
- Launch post drafts
- Outreach templates
- Terminal demo transcript
- Docs homepage screenshot
- Generated report screenshot
- Badge generator screenshot
- Report preview asset
- MCP setup screenshot asset
🛠️ Development
# Clone the repository
git clone https://github.com/ForkPoint/agent-lighthouse.git
cd agent-lighthouse
# Install dependencies
pnpm install
# Build all packages
pnpm build
# Run unit tests
pnpm test
📄 License
Apache-2.0 © ForkPoint
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