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Audit a page

audit_page

Start a full page audit. Spends credits (from 1.25 per page; call estimate_cost first for the exact price). Returns a job_id immediately. Poll with get_audit using that job_id until status is complete. Findings are grouped as priority / worth considering / not measured. Does NOT measure keyword ranks, backlinks, traffic, or Search Console data. Does NOT invent scores. Every action cites a real check id.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "audit_page"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesPublic http(s) URL.
site_idNoOptional. A site id from list_sites, to file the audit under that site.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / site_id / description
      Added value: +"Optional. A site id from list_sites, to file the audit under that site."
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses that it spends credits (1.25 per page), that it is asynchronous and returns job_id immediately, and that it does not measure keyword ranks, backlinks, traffic, or Search Console data. The statements that it does not invent scores and that every action cites a real check id add trust-relevant behavior not present in any structured field.

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?

Front-loads the action, then cost, then the async contract, then scope exclusions. Every sentence conveys a distinct operational fact with no 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?

For an async, credit-spending tool with no output schema, the description covers cost, return value (job_id), the polling workflow, and findings structure, plus explicit scope boundaries. Nothing an agent needs to invoke and follow up correctly is missing.

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%, so both url and site_id are already documented in the schema. The description adds no additional meaning about the parameters (it never mentions site_id filing behavior), so the baseline 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 and resource ('Start a full page audit') and immediately disambiguates from siblings by naming get_audit for polling and estimate_cost for pricing. An agent can distinguish this from crawl_site or check_vitals without opening any schema.

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

Usage Guidelines5/5

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

Explicitly directs the agent to call estimate_cost first for the exact price and to poll with get_audit using the returned job_id until status is complete. It also gives clear exclusion guidance about what the audit does not cover, leaving nothing to inference.

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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