SEO Score API

Deep Audit (wait for result)

deep_audit

Run a Deep Audit — a thorough, AI-assisted SEO audit that scores a URL across 9 dimensions (technical, crawlability, content/entity, Core Web Vitals, technical SEO, structured data, security, media, off-site): thousands of catalog checks plus up to 150 AI checks. Runs asynchronously server-side; this tool waits for the result (about 90 seconds once it starts, longer if queued). Included on Pro ($39/mo, 20/month) and Ultra ($99/mo, 100/month); other keys spend a purchased Deep Audit credit. For long waits use start_deep_audit + get_deep_audit instead.

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": "deep_audit"
  }
}

Input Schema

Name	Required	Description
`url`	Yes	URL to audit. Must include the protocol (https://...).
`business_type`	No	Optional. Tunes which checks apply; worked out from the page when omitted.
`timeout_seconds`	No	How long to wait before giving up (job keeps running).

Output Schema

Name	Required	Description	Default
`score`	No	Overall Deep Audit score.
`sections`	No	Per-section scores and findings.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false), the description discloses that execution is asynchronous server-side, that the call blocks roughly 90 seconds and longer if queued, and that credits are consumed — none of which is inferable from annotations or schema. The only modest gap is that it doesn't say what a failure or timeout response looks like, though the output schema covers the success shape.

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?

The core purpose and the sibling-routing guidance are front-loaded, and every sentence carries information (dimensions, async behavior, timing, cost, alternative). It is dense rather than bloated, though the long parenthetical list of nine dimensions plus the pricing sentence make it heavier than strictly necessary for selection.

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 a credit-consuming, blocking audit call, the description covers cost, latency, async semantics, and the non-blocking alternative, and an output schema exists so return values need not be explained. Nothing material is missing for an agent to decide and 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%, so all three parameters are already documented, including the enum values for business_type and the timeout semantics. The description adds no parameter-specific meaning (e.g., how business_type interacts with the nine dimensions, or how the timeout interacts with queueing beyond 'longer if queued'), 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?

The description opens with a concrete verb and resource ('Run a Deep Audit — a thorough, AI-assisted SEO audit that scores a URL across 9 dimensions') and enumerates the dimensions, so an agent knows exactly what it produces. It also names the specific siblings it must not be confused with (start_deep_audit + get_deep_audit), separating it from the rest of the catalog.

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?

It gives explicit routing: use this tool when you want to block on the result, and use start_deep_audit + get_deep_audit for long waits. It also states the cost conditions (Pro/Ultra quotas, or one purchased Deep Audit credit for other keys), which is exactly the when-to-use context an agent needs before spending a credit.

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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