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Website Audit (Tech, SSL, Accessibility, GDPR, Domain)

site_audit
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One call audits a site: tech stack, TLS certificate, accessibility (WCAG, grade), GDPR cookies and trackers before consent, domain and email security, optional screenshot. Returns a sorted issue list, grades and each section; a failed section is reported in checks while the others still return. Cheaper than calling the six checks separately. Set screenshot false to skip the image. Price: $0.055 USDC per call, paid inside this MCP call via x402 (USDC on Base, Solana, Polygon or Arbitrum). x402 MCP clients such as @x402/mcp pay automatically. Free sample: call with the example input {"url":"https://example.com","screenshot":false}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesSite URL or domain
screenshotNoInclude a 1280x800 screenshot as base64

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Adds substantial behavior beyond the annotations: the return shape (sorted issue list, grades, each section), graceful degradation on partial failure (a failed section is reported in checks while others still return), the screenshot opt-out, and the full payment model ($0.055 USDC via x402 on Base/Solana/Polygon/Arbitrum, auto-paid by x402 MCP clients). This is exactly the kind of cost/auth/failure context annotations do not carry.

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

Conciseness4/5

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

Front-loads the purpose and scope, then behavior, then pricing and the sample call. It is somewhat dense, especially the payment and free-sample sentences, but every element (cost, chains, degradation behavior) is actionable for an agent and nothing is redundant filler.

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

Completeness5/5

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

With no output schema, the description carries the return-value burden and does so, describing the sorted issue list, grades, per-section output, and partial-failure reporting. Combined with cost and payment mechanics, an agent has everything needed to invoke and interpret the call 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 description coverage is 100% with only two parameters, so the schema already documents url and screenshot. The description's 'Set screenshot false to skip the image' only restates the schema's default semantics and adds no new format or constraint detail, so the baseline of 3 applies.

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?

States a specific verb (audits) and resource (a site) and enumerates the exact sections covered: tech stack, TLS certificate, accessibility/WCAG, GDPR cookies and trackers, domain and email security. It also explicitly positions itself against siblings, noting it is cheaper than calling the six checks separately, so an agent can distinguish it from accessibility_check, ssl_check, tech_stack, and privacy_check.

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?

Gives clear when-to-use guidance (one call replaces the six individual checks, and it is cheaper) and a concrete free-sample invocation with an example input. It stops short of explicitly naming the alternative tools or stating when NOT to use this aggregate (e.g. when only one section is needed), so it is strong but not fully explicit.

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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