Agent skill

Agent Ready

by mblode in mblode/agent-skills

Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed…

MITAuto-check passedMarketing & SEO

Install Agent Ready

skills CLI
$ npx skills add mblode/agent-skills --skill agent-ready -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mblode/agent-skills agent-ready --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mblode/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/agent-ready .claude/skills/agent-ready && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-ready
GitHub stars
143
Token cost
~2.1k tokens
SKILL.md length
973 words
Files
7 (incl. scripts, references)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed…

  • Works in 5 steps: The map: llms.txt on the docs host, a… → Failures the product actually has (docs… → Warnings on those same surfaces… → …
  • Asked to make our site agent-ready
  • SKILL.md covers Contents, Workflow, Reference files and Priority, plus 2 more sections
  • Runs Shell scripts from its folder; calls npx; reaches isitagentready.com and llmstxt.org

What it does

Agent Ready is an agent skill from mblode/agent-skills. Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed URLs. Use when asked to "make our site agent-ready", "improve Agent Score", "fix llms.txt coverage", "agents keep 404ing on our docs", or when a pasted scorecard is the brief.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `evals/evals.json`, `references/api-surfaces.md` and `references/docs-afdocs.md`). Compatibility notes: The verification script needs Bash and curl. Scanner commands need Node.js and npm registry access.

It sits in Marketing & SEO, covering AI search optimization. The repository describes itself as: Nobody ships AI slop on purpose. These skills make sure you don’t. The licence is MIT.

When your agent uses it

  • Asked to make our site agent-ready
  • Improve Agent Score
  • Fix llms.txt coverage
  • Agents keep 404ing on our docs

Example prompts

  • “make our site agent-ready”
  • “improve Agent Score”
  • “fix llms.txt coverage”
  • “/agent-ready”

Requirements

  • Node.js
  • A Bash shell
  • Compatibility (from SKILL.md): The verification script needs Bash and curl. Scanner commands need Node.js and npm registry access.

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. The map: llms.txt on the docs host, a link to it in the first lines of every markdown twin, and Link headers that advertise both. Agents…
  2. Failures the product actually has (docs HTML that agents cannot read, HTML error pages on a real API, gated public docs with no alternate…
  3. Warnings on those same surfaces (llms.txt coverage, buried directives, wrong Content-Type).
  4. Recommended checks that match a surface already in the repo (OpenAPI, MCP, OAuth).
  5. Emerging extras (commerce protocols, A2A, DNS-AID) only when the product already offers them or the user asked to add them.

What it can do on your machine

Read from SKILL.md and the folder at commit cef4cfa. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • isitagentready.com
    • llmstxt.org

    Also links to:

    • github.com
    • is-agentic.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    The verification script needs Bash and curl. Scanner commands need Node.js and npm registry access.

    From compatibility in the SKILL.md frontmatter.

Context cost

Agent Ready loads about 2.1k tokens when it runs, and up to ~7k if it reads all its reference files. Until then it costs about 96 tokens; SKILL.md has 973 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mblode/agent-skills at commit cef4cfa, republished under its MIT licence (© mblode). 973 words, ~2,081 tokens.

Download SKILL.mdSave it as .claude/skills/agent-ready/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
agent-ready
description
Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed URLs. Use when asked to "make our site agent-ready", "improve Agent Score", "fix llms.txt coverage", "agents keep 404ing on our docs", or when a pasted scorecard is the brief.
compatibility
The verification script needs Bash and curl. Scanner commands need Node.js and npm registry access.

Agent Ready

Turn a public agent-readiness score, or a log of agents failing to navigate, into shipped, verified HTTP and docs changes.

  • IS: ingesting Mintlify Agent Score / AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench findings, plus server-side evidence of agent 404s, inspecting the repo, implementing the matching protocols, adding tests, and verifying live responses.
  • IS NOT: rewriting docs prose (ghostwriter), package/CLI/SDK ergonomics (dx-audit), whether an in-product agent can be trusted (ax-audit), search ranking, crawler policy, and Next.js llms.txt/markdown routes (seo; this skill owns the AFDocs and Is Agentic contract those routes must satisfy), or repo instruction files (agents-md). Do not vendor vercel-labs/is-agentic; that skill retrieves reports. This one implements the product.

Contents

Workflow

text
Agent-ready progress:
- [ ] Step 1: Ingest the report, the agent 404 log, or run scanners against the public URL
- [ ] Step 2: Inspect the existing codebase before any edit
- [ ] Step 3: Inventory every knowledge surface the origin serves and map each finding to a real one; skip surfaces the product does not offer
- [ ] Step 4: Load the matching reference and implement the map first, then failures, then warnings. For Next.js App Router `llms.txt` and markdown routes, load `seo` (that skill's `nextjs-implementation.md` and `answer-engines.md`) instead of a second recipe.
- [ ] Step 5: Add or update tests for every behavior you change
- [ ] Step 6: Verify every public endpoint and machine-readable file you touched (`scripts/check-surfaces.sh`, then the curl recipes for anything it does not cover)
- [ ] Step 7: Report changes, quoted verification, and remaining product decisions

A pasted scorecard is the spec. If none is present and the user named a public URL, gather one:

bash
npx afdocs check <docs-url> --format scorecard --sampling deterministic
npx is-agentic <domain> --json

Is It Agent Ready: POST https://isitagentready.com/api/scan with {"url":"<origin>","format":"agent"}. Prefer the user's pasted report over a new scan when both exist.

Server logs are a brief too. Agents fetch server-side and run no JavaScript, so they never appear in client-side analytics; count requests for .md URLs, llms.txt, and recognized AI user agents, and treat a stream of 404s from those agents (fetch, 404, guess a sibling path, retry) as the failing check. references/verification.md has the log queries and the navigation benchmark.

Step 3 covers the whole origin, not only /docs: changelog, release notes, help center, community, and status pages are knowledge agents answer from, and they are usually HTML-only while the docs are ready. Decide per surface whether it gets markdown twins and an index entry; marketing pages do not.

Preserve visual design and existing product behavior. Change discovery, representations, headers, and documented contracts, not the feature set.

Local test suites that cannot reach production are safe to run, fix, and rerun. Do not deploy, change DNS, buy a registry name, or write outside the working tree without authorization.

Done when every in-scope failing check has a code or content change (or an explicit skip with reason), tests cover the new behavior, and Step 6 quotes status, Content-Type, and the relevant headers or body from the environment you actually hit.

Reference files

FileRead when
references/docs-afdocs.mdMintlify Agent Score, AFDocs, llms.txt, .md URLs, the index link in markdown twins, Accept negotiation, page size, auth gates, non-docs knowledge surfaces
references/api-surfaces.mdIs Agentic API findings: JSON errors, OpenAPI, versioning, rate limits, function calling, CLI, MCP
references/site-discovery.mdIs It Agent Ready: robots, sitemap, Link headers, DNS-AID, well-known catalogs, bot rules
references/verification.mdStep 6: check-surfaces.sh, curl recipes, server-log measurement, url-discovery-bench, and what counts as evidence

Priority

Agents read markdown fine and fail at navigation. In Mintlify's 2026 benchmark (2,400 tasks, 20 docs sites, Claude and Codex) accuracy held at 94 to 99% in every format while failed requests per task went 2.23 on HTML, 1.42 on plain markdown, 0.11 once each markdown page linked llms.txt. Order work accordingly:

  1. The map: llms.txt on the docs host, a link to it in the first lines of every markdown twin, and Link headers that advertise both. Agents request .md and llms.txt only when they know they exist.
  2. Failures the product actually has (docs HTML that agents cannot read, HTML error pages on a real API, gated public docs with no alternate path).
  3. Warnings on those same surfaces (llms.txt coverage, buried directives, wrong Content-Type).
  4. Recommended checks that match a surface already in the repo (OpenAPI, MCP, OAuth).
  5. Emerging extras (commerce protocols, A2A, DNS-AID) only when the product already offers them or the user asked to add them.

A missing MCP card is not a failure on a site that has no MCP server. Do not invent an API, CLI, or payment protocol to chase points.

Show full SKILL.md (352 more words)Show less

Output

Group work by check. For each: evidence from the report, files changed, exact markup or schema added, verification quote, skip reason if N/A. When the brief was a 404 log or benchmark, quote failed requests per task before and after.

Finish with remaining items that need a product decision, DNS access, or credentials.

Gotchas

  • A .md twin has no navigation: the conversion stripped it with the chrome. Emit the llms.txt link from the twin route so no page can miss it; a per-page edit drifts.
  • Markdown twins are a route in one app. When the changelog or blog lives in a separate marketing app on the same origin, it stays HTML-only without anyone deciding that; walk every app, not only the one with the twin route.
  • One llms.txt advertised three ways (rel="llms-txt" from a proxy, rel="https://llmstxt.org/rel/llms-txt" from framework headers, rel="describedby" from a layout <link>) leaves the scanner reading whichever layer wins on that response. Pick the rel set the scanners probe and emit it from one place.
  • llms.txt that lists HTML while .md twins exist steers agents away from markdown and is scored worse than linking .md from the start.
  • A directive in <head>, nav, or past 50% of the HTML body does not count. Put it in the document body, near the top, server-rendered.
  • A dashboard with no agent traffic proves nothing: agents run no JavaScript, and Search Console and SERP tools count searchers, not agents. Server logs of .md, llms.txt, and AI user agent requests are the only readership measure; without a log drain the honest number is No data, not a client-side proxy.
  • Bot protection tuned for crawlers (challenge pages, WAF bot rules, tight rate limits on text/markdown routes) blocks the agents you are optimizing for, and they cannot pass a challenge. Exempt the machine-readable routes or serve them from paths the rules do not cover.
  • Coverage fail vs curated index: regenerate from the sitemap when the site intends parity; if the index is intentional, say so and do not pad it with marketing URLs.

Maintenance only: evals/evals.json is for changing this skill, not for a user task.

© mblode, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/agent-ready of mblode/agent-skills.

  • SKILL.md
  • evals/evals.json
  • references/api-surfaces.md
  • references/docs-afdocs.md
  • references/site-discovery.md
  • references/verification.md
  • scripts/check-surfaces.sh

Open the folder on GitHubat commit cef4cfa

Compare with similar skills

Agent Ready next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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SEO GeoReScienceLab/opc-skills1.8k4 repos~2.1kAutomated safety check: PassApache-2.0
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude11k—~2.8kAutomated safety check: NotesMIT
GEO Monthly Delta Reportzubair-trabzada/geo-seo-claude11k—~2.4kAutomated safety check: NotesMIT
SEO DataforseoAgriciDaniel/codex-seo7912 repos~4.6kAutomated safety check: PassMIT

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Categories

Questions about Agent Ready

What does Agent Ready do?

Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed…. Agent Ready is an agent skill from mblode/agent-skills. Implements agent-readiness on public sites and docs from Mintlify Agent Score, AFDocs, Is Agentic, Is It Agent Ready, or url-discovery-bench reports, or from server logs of agents 404ing on guessed URLs.

When should I use Agent Ready?

Agent Ready fits situations like: asked to make our site agent-ready; improve Agent Score; fix llms.txt coverage; agents keep 404ing on our docs.

How do I install Agent Ready in Claude Code?

Run `npx skills add mblode/agent-skills --skill agent-ready -a claude-code`. Or copy the skill folder (skills/agent-ready in mblode/agent-skills) into .claude/skills/agent-ready in your project. Claude Code loads it when a task matches its description.

How do I install Agent Ready in Codex?

Run `npx skills add mblode/agent-skills --skill agent-ready -a codex`. Or copy the skill folder (skills/agent-ready in mblode/agent-skills) into .agents/skills/agent-ready in your project. Codex loads it when a task matches its description.

Can I use Agent Ready in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mblode/agent-skills --skill agent-ready -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-ready, .gemini/skills/agent-ready, .github/skills/agent-ready and .opencode/skills/agent-ready in your project.

What does Agent Ready need to run?

Going by SKILL.md and its folder, Agent Ready needs a shell for the scripts in its folder and the command-line tools its instructions call (npx). Our summary lists: Node.js; A Bash shell. Compatibility (from SKILL.md): The verification script needs Bash and curl. Scanner commands need Node.js and npm registry access..

Does Agent Ready access the network?

SKILL.md names 4 domains. In commands or code: isitagentready.com and llmstxt.org; the agent is likely to contact these when it follows the instructions. As links in the text: github.com and is-agentic.com. This is read from the text; nothing was executed.

Is Agent Ready safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Agent Ready use?

Agent Ready is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Ready use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.

What are the alternatives to Agent Ready?

Skills that share tags, products or a category with Agent Ready: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and GEO Monthly Delta Report (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Ready?

mblode (a GitHub user) maintains it in mblode/agent-skills, which has 143 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 6, 2026.

Source: mblode/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.