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Agent Data API

company_enrich

Company enrichment from a domain (firmographics + tech stack) in ~2 s: name, description, logo, socials (LinkedIn, X, Instagram...), contact emails and phones, address, key pages (pricing, careers, docs, login), website platform, email provider, DMARC, and the SaaS stack proven by DNS records (~200 vendors: Google Workspace, Microsoft 365, HubSpot, Salesforce, Atlassian, OpenAI...) plus website tech. No API key. Price: $0.01 per call (x402, USDC).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and discloses useful traits: ~2 s latency, no API key, x402/USDC pricing at $0.01 per call, and data sources including DNS records. It does not explicitly discuss permissions, rate limits, or data freshness, but it is far more transparent than a bare mutation/read label.

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 front-loaded with the core capability and packs useful output examples, latency, price, and payment details into one dense sentence. The long enumeration of fields is justified by the absence of an output schema, though it could be structured more scannably.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Because there is no output schema, the description usefully enumerates returned fields, including firmographics, socials, contacts, pages, and SaaS stack. It is complete enough for an agent to understand the value, though input format and error behavior are not covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has one required string parameter with 0% description coverage, so the description must compensate. It only repeats that the input is a domain; it does not specify whether a bare domain, URL, or subdomain is expected, nor give format examples.

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 specific verb and resource: company enrichment from a domain, with firmographics and tech stack. It is clearly distinct from the sibling tools in practice, but it does not explicitly name or differentiate alternatives, so it falls short of the top score.

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?

The description implies usage by saying enrichment is keyed off a domain and noting speed and price. However, it gives no explicit when-to-use guidance, no exclusions, and no comparison to alternatives such as web_search or email_verify.

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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