check_agent_readinessRead-only audit of whether a public website is ready for AI agents: crawler access, llms.txt, structured data, discovery files, and metadata. Returns a 0-100 score and specific gaps. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Website URL to audit (https://...). |
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| kind | No | ||
| score | No | ||
| checks | No | ||
| blocked | No | ||
| disclaimer | No | ||
| dataUseNotice | No |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "blocked": {
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ },
+ "checks": {
+ "items": {
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "dataUseNotice": {
+ "type": "string"
+ },
+ "disclaimer": {
+ "type": "string"
+ },
+ "kind": {
+ "type": "string"
+ },
+ "score": {
+ "type": "number"
+ },
+ "url": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, open-world, and non-destructive behavior. The description adds meaningful context beyond that: it returns a 0-100 score and specific gaps, and it is free. This gives an agent a clear idea of what invoking the tool will produce.
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?
The description is two tight sentences, front-loads the read-only nature, lists the audit dimensions, and states the output form. No filler or redundancy.
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 read-only audit tool with a rich description, full schema coverage, annotations, and an output schema, the description is complete. An agent has what it needs to select and invoke 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 description coverage is 100% for the single url parameter, so the schema already handles parameter documentation. The description adds only a slight contextual nuance ('public website') without providing additional parameter semantics.
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 states a specific verb ('audit'), the target resource ('public website'), and the scope ('AI agent readiness') with concrete checklist items. It is clear on its own, but it does not explicitly distinguish itself from the sibling tool check_ai_visibility.
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 intended use case is implied: use this to audit a public website's AI-readiness and get a readiness score. However, there is no explicit guidance on when to prefer this over check_ai_visibility or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.