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AIsa Backlinks

Bulk Referring Domains

post_dataforseo_backlinks_bulk_referring_domains_live
Destructive

This endpoint will provide you with the number of referring domains pointing to domains, subdomains, and pages specified in the targets array. The returned numbers are based on all live referring domains, that is, total number of domains pointing to the target with any type of backlinks (e.g., nofollow, noreferrer, ugc, sponsored etc) that were found during the latest check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

The annotations already declare the safety profile (openWorldHint=true, destructiveHint=true, idempotentHint=false), and the description does not contradict them. It adds useful domain context about what the returned numbers represent (all live referring domains, any backlink type, latest check), but says nothing about billing cost, rate limits, or asynchronous behavior expected from a live POST endpoint.

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?

Two sentences, front-loaded with the core purpose, no filler or repetition. Slightly dense but every clause contributes to understanding the returned metric.

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?

An output schema exists so return shape need not be explained, and annotations cover safety. Still, for a bulk live POST endpoint the description lacks targeting limits, billing/credit implications, and any routing hint among the many similar backlinks siblings, leaving meaningful gaps.

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?

Top-level schema coverage is 0% for the single 'body' parameter, so the description should carry explanatory weight. It does clarify that targets are domains, subdomains, and pages, but omits the operational details (up to 1000 targets, no https://www for domains, absolute URL required for pages) that live only in the nested schema text.

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 uses a specific verb-and-resource framing: it returns the count of referring domains pointing to the targets supplied. It also distinguishes its scope (all live referring domains regardless of link type), which helps separate it from the 'new/lost' sibling. However, it never names or contrasts with the non-bulk referring_domains_live or the new/lost variant, leaving the agent to infer sibling differences.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to choose this tool over the many sibling backlink endpoints, nor any prerequisite or exclusion information. The 'bulk' and 'live' semantics imply multi-target, current-snapshot usage, but that is left entirely 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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