Checks whether a website has a usable llms.txt. Score 0–100. Free 3/day/IP, then ¥10.
Scored across 1 tool
There is only one tool, so there is no possibility of confusion or overlap with other tools. The tool's purpose is clearly defined in its name and description.
The single tool name follows a clear verb_noun snake_case pattern. With only one tool, there are no mixed conventions or inconsistent naming styles to reduce coherence.
One tool feels thin for something called a 'Gateway', but the tool itself is focused and serves a specific purpose. It is borderline rather than egregiously insufficient.
The tool covers the core operation of checking an llms.txt file and returning a score. Minor gaps exist, such as no way to retrieve raw content, batch-check multiple domains, or manage API keys.
Fetch https://{domain}/llms.txt, report whether it exists, basic shape, and a 0–100 score. Free: 3/day/IP. Paid: X-API-Key, ¥10 per call.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Website host, e.g. example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It discloses that the tool performs an HTTP fetch, reports existence and shape, returns a 0–100 score, and specifies free usage limits and paid authentication via X-API-Key. It could clarify how failures or absence are represented, but the core behavior is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences deliver the action, the result summary, the score, and the rate-limit/auth details with no filler. The core behavior is front-loaded, and every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description covers the essential operational details: what is fetched, what is returned, the free quota, and paid access. The phrase 'basic shape' is somewhat vague, but an agent has enough to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds meaning by showing how the domain parameter is used to construct the URL (https://{domain}/llms.txt), clarifying that the parameter is a hostname inserted into a fixed URL rather than a full URL.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: 'Fetch https://{domain}/llms.txt' and report existence, shape, and score. It clearly distinguishes the tool's function even without sibling tools to compare against.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes clear this is the tool for checking a site's llms.txt and getting a score, with no alternatives listed. It does not explicitly state when not to use it, but the absence of siblings makes the intended usage clear from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
check_llms_txtChecks llms.txt, AI crawler access in robots.txt, and sitemap - with a 0-100 AI readiness score.
Scores any public website on how usable it is by AI agents, with per-check evidence.
Check website AI-readiness: Schema.org, llms.txt, E-E-A-T, robots.txt. Works in Cursor & Claude.
Scan any website's AI readiness: AI search visibility and AI agent usability. Free, no auth.
Add one secure layer between your agents and this server.
