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AIsa SEO & AI Visibility

OnPage API Summary

get_dataforseo_on_page_summary
Read-onlyIdempotent

Using this function, you can get the overall information on a website as well as drill down into exact on-page issues of a website that has been scanned. As a result, you will know what functions to use for receiving detailed data for each of the found issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYestask identifier required field you can get this ID in the response of the Task POST endpoint example: “07131248-1535-0216-1000-17384017ad04”

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / id / description
      Previous value: -"DataForSEO task ID."New value: +"task identifier required field you can get this ID in the response of the Task POST endpoint example: “07131248-1535-0216-1000-17384017ad04”"
  2. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds one piece of real context — that the site must already have been scanned, implying the task id refers to a completed Task POST — but says nothing about result freshness, pagination, or failure states of an incomplete task.

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

Conciseness3/5

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

Two sentences, but the lead-in 'Using this function, you can' is pure filler before the actual content arrives, and 'drill down into exact on-page issues' overstates what a summary endpoint returns. The second sentence carries the real value and should have led.

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?

With an output schema present and read-only annotations, return values and safety need no explanation here. What is missing is sibling routing among the many get_*/post_* OnPage tools, which is the main open question an agent would have when selecting this tool.

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?

There is one parameter with 100% schema description coverage, and the schema already explains that 'id' is the task identifier obtained from the Task POST response. The description adds nothing about the id, so the baseline 3 for full schema coverage applies.

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

Purpose4/5

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

The description states a recognizable verb+resource: retrieving overall on-page information for a website that has been scanned. It frames the result as a summary view that precedes the detail tools, which gives it an identity distinct from the post_* detail endpoints. It does not, however, explicitly distinguish itself from the generic sibling get_details.

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?

It implies a workflow — call this first to learn which functions to use for detailed data on each issue — which is genuinely useful routing context. But it never names an alternative tool or states an explicit when-not condition, so the guidance stays at the implied level rather than actionable selection criteria.

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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