agent-ready

agent-ready is a skill for Claude Code, Codex from mlava/agent-ready-mcp. It costs 122 tokens per session (1,647 once invoked), scanned A, original, MIT.

Instructions for checking how well a website can be understood by AI agents and AI search systems.

In plain words
What is it for?
Auditing items such as llms.txt, robots.txt, structured data, sitemaps, and agent or MCP descriptions.
Why use it?
They replace guesswork with a fresh review of files and metadata that help agents discover and interpret a website.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions AGENTS.md.

Good fit Auditing items such as llms.txt, robots.txt, structured data, sitemaps, and agent or MCP descriptions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mlava/agent-ready-mcp/agent-ready
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 mlava/agent-ready-mcp --skill agent-ready
Clone the repo
git clone --depth 1 https://github.com/mlava/agent-ready-mcp

Made for: Claude Code, 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 agent-ready

README.md
[![agentmods](https://agentmods.dev/badge/skills/mlava/agent-ready-mcp/agent-ready/github.svg)](https://agentmods.dev/skills/mlava/agent-ready-mcp/agent-ready)
Your own site
<a href="https://agentmods.dev/skills/mlava/agent-ready-mcp/agent-ready"><img src="https://agentmods.dev/badge/skills/mlava/agent-ready-mcp/agent-ready/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for agent-ready

Your own site · 80×15
<a href="https://agentmods.dev/skills/mlava/agent-ready-mcp/agent-ready"><img src="https://agentmods.dev/badge/skills/mlava/agent-ready-mcp/agent-ready.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,647 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 $0.00122 $0.01647
Opus 5.5 $0.00049 $0.00659
Sonnet 5.5 $0.00024 $0.00329
Haiku 4.5 $0.00012 $0.00165

Measured 2mo ago against content hash 05b9c1f25e28, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

agent-ready 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 2mo 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/agent-ready/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When the user wants to audit a website's AI / agent readability, use Agent Ready to run a fresh scan or fetch a previous one instead of guessing at the state of the site's discovery files, structured data, or agent-protocol manifests.

When to Use This Skill

Activate this skill when the user:

  • Asks how AI-readable a website is, or wants a score against the Vercel Agent Readability Spec or the llmstxt.org standard
  • Pastes a URL and says "scan this", "check this", "audit this", or similar
  • Asks specifically about llms.txt, AGENTS.md, sitemap.md, robots.txt (AI bots), /.well-known/mcp.json, /.well-known/agent-card.json, agents.json, agent-permissions.json, UCP profiles, x402 payment endpoints, or markdown mirrors
  • Wants a prioritised list of fixes to make their site more visible to AI agents and AI search engines
  • References a previous scan by id and wants to interpret, compare, or generate fixes from it

How to Use

Step 1: Pick the right tool

  • scan_site — when the user wants a fresh agent-readability scan. Takes a URL (and an optional pageLimit). Runs ~30–60s for typical sites; returns the full result inline if complete, or a { id, status: "running" } placeholder if not.
  • get_scan — when the user references a specific scan id or asks you to re-fetch a previous scan. Returns the same result shape as scan_site when complete.

For end-to-end "scan + interpret + plan fixes" workflows, the server also exposes three prompts that wire these tools together:

  • scan — fresh scan + high-level summary
  • interpret_scan — plain-English explanation of a scan's findings
  • remediation_plan — prioritised fix-it doc (optional focus: "seo" or "agents")

If the user describes one of these flows, surface the corresponding prompt name rather than reconstructing the workflow yourself.

Step 2: Pass the URL verbatim

Pass the user's URL exactly — including scheme, path, and trailing slash. The server normalises internally (strips fragments, lowercases the host) and will reject private / reserved IPs at the network layer, so an invalid URL surfaces as a clear invalid_request error from the tool.

Read the full file on GitHub · 89 lines

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. 2mo ago First seen · 89 lines · 122 tokens per session scan A 05b9c1f25e28

Subscribe to this mod's changes

agent-ready is a skill published in the GitHub repository mlava/agent-ready-mcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 122 tokens to every session and 1,647 once invoked, about $0.0005 per session on Opus 5.5. 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

agent-ready compared with skills from other repositories

agent-ready next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
agent-readymlava/agent-ready-mcpSkill22mo agoMITA122Claude Code, Codex
omni-inferencediegosouzapw/OmniRouteSkill83k6d agoMITA47Claude Code, Codex
omni-settingsdiegosouzapw/OmniRouteSkill83k6d agoMITA31Claude Code, Codex
cli-servediegosouzapw/OmniRouteSkill83k6d agoMITA39Claude Code, Codex
omni-providersdiegosouzapw/OmniRouteSkill83k6d agoMITA45Claude Code, Codex
cli-providersdiegosouzapw/OmniRouteSkill83k6d agoMITA36Claude Code, Codex
omni-authdiegosouzapw/OmniRouteSkill83k6d agoMITA36Claude Code, Codex