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Check domain authority (coming soon)

check_domain_authority
Read-only

Get a domain authority score from 0 to 100 based on Common Crawl web data to help you vet outreach and link-building prospects.

Instructions

COMING SOON: this Kanto Labs actor is not public on the Apify Store yet. Until it is, calls return an 'actor not yet public' error and nothing is charged. Score how authoritative (well linked) domains are: a 0-100 authority score computed from the open Common Crawl domain web graph of about 133 million domains, with the harmonic-centrality rank, PageRank rank, top-% percentile, number of subdomains seen, and the rank change and trend (up/down/stable/new) against the previous monthly graph. Accepts domains, URLs or email addresses; each is reduced to its registrable domain. Use it for link-building and outreach prospect lists, guest-post or PR vetting, expired-domain research, lead scoring and competitor tracking. It is its own open metric, NOT Moz Domain Authority or Ahrefs Domain Rating: compare domains against each other. It does not return backlinks and visits no website. Domains outside the top 12 million come back with ranked=false (score below 20) and are free. Thousands of domains finish in seconds. Cost: $0.001 per domain scored, billed to your Apify account; unranked and invalid domains are free. Runs the Apify actor kantolabs/domain-authority-checker with your APIFY_TOKEN; maxTotalChargeUsd caps the spend per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainsYesDomains, URLs or email addresses, e.g. ["stripe.com", "https://www.nytimes.com/section/world", "ceo@shopify.com"]. Reduced to the registrable domain; duplicates are removed.
timeoutSecsNoGive up after this many seconds (max 300, Apify's limit for synchronous runs). Default 280. For big batches, split the input into several calls.
maxTotalChargeUsdNoHard spending cap for this call in USD, enforced by Apify: the run stops once it has charged this much. Default 1 (server setting KANTO_MAX_CHARGE_USD).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds far richer behavioral context: current 'coming soon' status and error behavior, cost per domain, free unranked/invalid domains, performance expectations ('thousands of domains finish in seconds'), the underlying Apify actor and APIFY_TOKEN requirement, and the maxTotalChargeUsd hard cap. Nothing contradicts the annotations; the description exceeds the transparency burden.

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 description is long (~250 words) and front-loads the critical 'coming soon' status and error/charge behavior, then moves through definition, use cases, exclusions, and pricing in a logical order. Nearly every sentence adds a distinct piece of information, but there is slight redundancy (e.g., maxTotalChargeUsd is already described in the schema) and the text could be tightened without losing value.

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?

There is no output schema, yet the description enumerates the return values in prose: authority score, harmonic-centrality rank, PageRank rank, top-% percentile, subdomain count, and rank change/trend, plus the ranked=false state for unranked domains. It also covers input constraints, cost, timeout, availability, and response behavior, giving an agent sufficient context to invoke the tool and interpret results.

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 description coverage is 100%, so the baseline is 3. The description enriches the parameters by explaining input normalization to registrable domains, duplicate removal, the ranked=false threshold (score below 20), and cost/spend-cap semantics tied to maxTotalChargeUsd. It does not add JSON syntax details, but it adds meaningful behavioral meaning beyond the schema.

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 uses a specific verb ('Score') and precisely defines the resource and output: a 0-100 authority score computed from the Common Crawl web graph. It further distinguishes itself by stating it is an independent open metric, NOT Moz Domain Authority or Ahrefs Domain Rating, and clarifies that it does not return backlinks or visit websites. Even without naming sibling tools, it is behaviorally unique and clear.

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

Usage Guidelines4/5

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

The description provides explicit use cases: 'Use it for link-building and outreach prospect lists, guest-post or PR vetting, expired-domain research, lead scoring and competitor tracking.' It also gives negative guidance ('does not return backlinks and visits no website'), which tells an agent when not to choose it. However, it never names alternative sibling tools or states 'if you need X, use Y', so it stops short of full tool-selection routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.