π Quickstart & Installation
Run instant agentic readiness audits with zero installation or embed the scanner into your CI pipeline.
1. Instant Execution (Zero Install)
Use npx to audit any live storefront or staging environment in seconds:
2. Global / Project Installation
Install the CLI globally or save as a project developer dependency:
ποΈ Core Architecture
High-performance GathererβAuditβScorer execution pipeline.
Key Principle: Network I/O and HTML parsing occur strictly in Gatherers. Audits receive an immutable CheckContext and execute as pure, fully offline-testable functions.
π Scoring & 4 Readiness Vitals
How Agent Lighthouse evaluates readiness across key commerce pillars.
π Commerce Readiness (40%)
Weight: 0.40Evaluates Schema.org Product, Offer, Price, Availability, Brand, WebMCP commerce actions, and product field integrity.
π Content Discoverability (25%)
Weight: 0.25
Verifies /llms.txt, /llms-full.txt, sitemaps, Markdown alternates, and RSS feeds.
π€ Bot Accessibility (20%)
Weight: 0.20Checks AI crawler permissions (GPTBot, ClaudeBot, PerplexityBot), absence of aggressive bot walls, and non-blocking forms.
π Technical & Security (15%)
Weight: 0.15Audits HTTPS, HSTS, CSP, X-Content-Type-Options, CORS on AI files, server-rendered HTML, and fast response times.
π Interactive Audit Directory
Explore all 207 audits with evaluation rules, guidance, and remediation code snippets.
π» CLI Flags & CI Assertions
Options, presets, and budget assertions for terminal and CI runs.
| Flag | Default | Description |
|---|---|---|
| -p, --preset <name> | full | Audit preset (ecommerce, saas, quick, full). |
| -o, --output <formats> | terminal,html,json | Comma-separated output formats: terminal, html, json, md. |
| -d, --output-dir <path> | ./reports | Output directory for generated reports. |
| -v, --view | false | Automatically open the generated HTML report in the default browser. |
| --min-score <n> | 0 | Minimum score (0β100) required to pass CI assertions (exits code 1 if failed). |
| --assert-category <id:n> | - | Category-specific budget (e.g. --assert-category structured-data:90). |
| --debug-audit <id> | - | Print deep diagnostic breakdown for specific audit ID (e.g. 3.8) or fails. |
| -c, --config <path> | auto | Path to configuration file (agent-lighthouse.config.json). |
| --silent | false | Suppress terminal progress output. |
π¦ Node.js / TypeScript SDK
Integrate Agent Lighthouse scanning and HTML report generation programmatically.
import { runScan } from '@forkpoint/agent-lighthouse-core';
import { generateHtmlReport, generateMarkdownSummary } from '@forkpoint/agent-lighthouse-report';
import { writeFileSync } from 'node:fs';
// 1. Run live scan
const report = await runScan('https://yourstore.com', {
onEvent: (event) => {
if (event.type === 'phase:done') {
console.log(`[${Math.round(event.fraction * 100)}%] ${event.phase} done`);
}
},
});
console.log(`Overall Readiness Score: ${report.overallScore}/100 (${report.scoreTier})`);
// 2. Generate standalone Lighthouse HTML report
const html = generateHtmlReport(report);
writeFileSync('./reports/agent-report.html', html);
// 3. Generate Markdown summary for PR comments
const markdown = generateMarkdownSummary(report);
console.log(markdown);
π€ Model Context Protocol (MCP) Server
Enable AI coding assistants (Claude Desktop, Cursor, Antigravity) to audit and fix stores interactively.
Claude Desktop & IDE Configuration
{
"mcpServers": {
"agent-lighthouse": {
"command": "npx",
"args": ["-y", "@forkpoint/agent-lighthouse-mcp"]
}
}
}
π‘οΈ GitHub Actions CI Pipeline
Automate agentic readiness regression testing on every pull request.
name: Agent Lighthouse Audit
on:
pull_request:
branches: [main]
jobs:
audit:
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Run Agent Lighthouse Audit
run: |
npx @forkpoint/agent-lighthouse https://staging.yourstore.com \
--preset ecommerce \
--min-score 80 \
--output terminal,html,json,md \
--output-dir ./reports
- name: Upload HTML Report Artifact
uses: actions/upload-artifact@v4
with:
name: agent-lighthouse-report
path: ./reports/agent-lighthouse-report.html
π Interactive Report Inspector
Drag and drop any scan JSON report to view the interactive score gauges and category breakdown.
agent-lighthouse-report.json hereπ 100-Store Benchmark Findings
Key takeaways from our empirical audit of 100 top e-commerce storefronts.
llms.txt or full-text AI filesBenchmark Story
- The agentic gap: top storefronts have basic SEO, but rarely expose machine-readable action surfaces.
- Discovery gap: only a small minority expose
/llms.txtor/llms-full.txt. - Fastest boost: add
/llms.txt, an AI catalog, and accessible icon button names.
Post-ready Angle
Most commerce sites are built for human browsers and classic crawlers. Agent Lighthouse measures the layer needed for autonomous shopping agents: discovery files, crawler permissions, structured facts, and safe action paths.
Read benchmark notes →π Public Score Showcase
Shareable examples for launch posts, client before/after reports, and community submissions.
Good llms.txt, semantic structure, and crawler access make docs easier for AI coding agents to cite.
Product schema is common, but OpenAPI, WebMCP, and clean machine-readable checkout paths are usually missing.
Adding AI discovery files, crawler policy clarity, and accessible controls creates a visible score jump.
Submit a score and remediation notes so other teams can learn from real examples.
π·οΈ Badge Generator
Create a README badge for public site scores and before/after launch posts.
π£ Launch Kit
Ready-to-use copy and assets for Show HN, Product Hunt, Reddit, Dev.to, and outreach.
Builder-focused title and comment with a direct command users can try.
Name, tagline, description, and maker comment.
Value-first community drafts with affiliation disclosure.
Email and DM copy for SEO agencies, DevRel, and ecommerce platforms.