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agent_site_audit

Paid via standard x402 v1 (USDC on Base): audit ONE public site across eight AI-agent readiness surfaces (robots.txt, sitemap.xml, llms.txt, llms-full.txt, agents.txt, x402, agents.json, security.txt) and get a grade A-D. Price 2.00 USDC on Base.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesabsolute https URL of the site to audit

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden, and it discloses the most important behavior: this is a paid operation (x402 v1, 2.00 USDC on Base) with a defined outcome (grade A-D) and defined coverage (eight surfaces). It does not disclose failure modes (e.g., unreachable site, payment failure) but the monetary side effect is clearly flagged up front.

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?

The entire definition is one tight sentence that front-loads the payment requirement and then delivers scope, coverage list, output, and price with no filler. Every clause earns its place.

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

Completeness3/5

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

For a one-parameter tool this is close to complete: payment mechanics, scope, and the grade output are all stated. However, there is no output schema and the return payload beyond 'grade A-D' is unspecified, and the x402 payment flow is named but not explained, leaving an agent to infer the rest.

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

Parameters4/5

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

Schema coverage is 100% for the single required 'url' parameter, so the baseline is 3. The description adds the meaningful constraint that the target must be a 'public' site and exactly ONE, which is semantic value beyond the schema's 'absolute https URL' wording.

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 pairs a specific verb ('audit') with a concrete resource ('ONE public site') and enumerates the exact scope: eight named AI-agent readiness surfaces. It also states the expected outcome (a grade A-D) and the price, so an agent immediately understands what the tool does. The capitalized 'ONE' implicitly distinguishes it from the multi-site sibling agent_site_audit_5.

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

Usage Guidelines3/5

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

The description implies usage context — single public site, paid at 2.00 USDC via x402 v1 — but never explicitly says when to pick this over siblings like agent_site_audit_5 or web_fetch. The payment and 'ONE site' constraints give an agent enough to self-select for a single-site audit, but there is no when-not-to-use guidance.

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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