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agentlint

Audit any website for AI/agent-friendliness using AgentLint. Run `npx @cjavdev/agent-lint` with a URL to scan a site across 17 rules in 5 categories (transport, structure, tokens, discoverability, agent), get a 0-100 AgentScore with letter grade, and receive a prioritized remediation plan. Use this skill when: auditing a site for AI readiness, checking if a site has llms.txt or markdown support, improving a website's agent-friendliness score, fixing AgentLint violations, or understanding what makes a site AI-friendly. Trigger phrases: 'run agentlint', 'audit site for AI', 'check agent-friendliness', 'agentlint scan', 'AI-friendly audit', 'check llms.txt', 'agent readiness'.

100

Quality

100%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

AgentLint

Audit websites for AI/agent-friendliness. Runs 17 rules across 5 categories, produces a 0-100 AgentScore, and guides remediation.

Workflow

Step 1: Run the CLI

npx @cjavdev/agent-lint <url> --agent

The --agent flag outputs a structured markdown report optimized for parsing. If the user wants raw JSON, use --json instead.

Common flags:

FlagDefaultDescription
--max-depth <n>3Maximum crawl depth
--max-pages <n>30Maximum pages to crawl
--jsonOutput as JSON
--agentOutput agent-friendly markdown
--config <path>Path to config file

Exit codes: 0 = no errors found, 1 = errors found, 2 = invalid input/system error.

Step 2: Parse Results

Extract from the CLI output:

  • Score (0-100) and letter grade (A/B/C/D/F)
  • Violations grouped by severity: errors, warnings, info
  • Per-page details for page-specific violations

Step 3: Present Remediation Plan

Prioritize fixes by impact:

  1. Errors first (-10 pts each) — These are the biggest score killers
  2. High-ROI warnings (-4 pts each) — Fix easy ones first (e.g., adding a sitemap vs. restructuring content)
  3. Info items (-1 pt each) — Nice-to-have improvements

For each violation, provide:

  • What's wrong and why it matters
  • Concrete fix steps (reference references/remediation-guide.md for detailed instructions)
  • Expected score improvement

Score Interpretation

GradeScoreMeaning
A90-100Excellent. Site is highly agent-friendly.
B80-89Good. Minor improvements possible.
C70-79Fair. Several gaps in agent-friendliness.
D60-69Poor. Significant barriers for AI agents.
F0-59Failing. Major issues across multiple categories.

Scoring formula: Start at 100. Subtract 10 per error, 4 per warning, 1 per info. Clamped to 0-100.

Rule Quick Reference

Errors (-10 pts each)

Rule IDWhat It Checks
transport/accept-markdownReturns markdown for Accept: text/markdown
discoverability/llms-txt/llms.txt exists

Warnings (-4 pts each)

Rule IDWhat It Checks
transport/content-type-validValid Content-Type header on responses
transport/robots-txt/robots.txt exists (AI agent blocks are info)
structure/heading-hierarchyH1 exists, no skipped heading levels
structure/anchor-idsHeadings have anchor IDs for deep linking
tokens/page-token-countPage under 4,000 tokens (configurable)
tokens/boilerplate-duplication<30% repeated nav/header/footer content
agent/agent-usage-guidePages mention AI/agent keywords

Info (-1 pt each)

Rule IDWhat It Checks
structure/semantic-htmlUses <main>, <article>, or <section>
structure/meta-descriptionHas <meta name="description">
structure/lang-attribute<html lang="..."> attribute present
tokens/nav-ratioNav tokens <20% of page tokens
agent/mcp-detect/.well-known/mcp.json exists
discoverability/sitemap/sitemap.xml exists
discoverability/openapi-detectOpenAPI spec at common paths
discoverability/structured-dataJSON-LD structured data present

Prioritization Logic

When presenting a remediation plan, order fixes by points recoverable per unit of effort:

Quick wins (fix first):

  • discoverability/llms-txt — Create a single file, recover 10 pts
  • structure/lang-attribute — One-line HTML change, recover 1 pt
  • structure/meta-description — Add meta tags, recover 1 pt per page
  • discoverability/sitemap — Most frameworks auto-generate this

Medium effort:

  • transport/content-type-valid — Usually a server config fix
  • structure/heading-hierarchy — HTML structure fixes
  • structure/anchor-ids — Add a rehype/markdown plugin
  • agent/agent-usage-guide — Write a dedicated docs page
  • transport/robots-txt — Create/update a text file

High effort, high impact:

  • transport/accept-markdown — Requires server-side content negotiation (10 pts)
  • tokens/page-token-count — May require content restructuring
  • tokens/boilerplate-duplication — Requires template/layout changes

Configuration

Sites can customize behavior via agent-lint.config.json:

{
  "maxDepth": 3,
  "maxPages": 30,
  "tokenThreshold": 4000,
  "ignorePatterns": ["/blog/*"],
  "rules": {
    "tokens/page-token-count": {
      "severity": "info",
      "ignorePaths": ["/docs/changelog"]
    }
  }
}

Detailed Remediation

For step-by-step fix instructions with code examples for each rule (Nginx, Cloudflare Workers, Next.js, Express, static HTML), see references/remediation-guide.md.

Repository
cjavdev/agent-lint
Last updated
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