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Scan a site for AI agent readability

scan_site
Read-onlyIdempotent

Scan any public URL to get an AI agent readability score and per-check remediation hints. Identifies issues and provides guidance to improve agent-readiness.

Instructions

Runs the agent-ready.dev scanner against a URL and returns structured results: Vercel score, llmstxt.org score, and per-check findings with remediation hints. Scans may take up to ~60s; if the local poll deadline elapses, the tool returns the scan id and asks you to poll with get_scan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFully-qualified URL to scan, including scheme (https://...).
pageLimitNoOptional maximum number of pages to crawl from the root URL. Capped by your plan (Free 25, Pro 250, Team 2000).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
statusYes
rootUrlNo
createdAtNo
completedAtNo
pagesDiscoveredNo
pagesScannedNo
vercelScoreNo
vercelRatingNo
llmstxtScoreNo
siteChecksNo
llmstxtChecksNo
pageResultsNo
shareTokenNo
urlNo
pollUrlNo
messageNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, idempotent, open-world. The description adds behavioral details: potential 60s delay and fallback polling behavior. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with core functionality. Every sentence adds value: first describes the action and outputs, second describes timing and fallback. No waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Description covers inputs, outputs, timing, and fallback behavior. Output schema exists so return values need not be detailed. Complete enough for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters described. The description adds context about the scanner and results but does not provide additional syntactic semantics beyond the schema. Baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs the agent-ready.dev scanner against a URL, listing specific outputs (Vercel score, llmstxt.org score, per-check findings). It distinguishes itself from sibling tools by mentioning polling with get_scan when the scan is not complete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description explains that scans may take up to ~60s and if the local poll deadline elapses, returns a scan ID for polling with get_scan. This provides clear context for when to use this tool and when to follow up with get_scan.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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