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interzoid_private_company_deal_intel

Read-onlyIdempotent

Private company deal intelligence: funding rounds, total funding raised, latest valuation, key investors, revenue estimate, growth metrics, employee count estimate, recent deals and exits, comparable companies, industry, founding year, and headquarters, with data confidence notes. For venture capital, private equity, M&A research, and investor prospecting. Cost: $0.25 USDC via x402.

Input Schema

NameRequiredDescriptionDefault
lookupYesPrivate company name
languageNoOptional. Two-letter code for results in that language (default English): fr, de, it, es, ja, pt, zh, ar, nl, el, tr, ko, sv, vi, th, id. Same price in every language.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / language
      Added value: +{
      +  "description": "Optional. Two-letter code for results in that language (default English): fr, de, it, es, ja, pt, zh, ar, nl, el, tr, ko, sv, vi, th, id. Same price in every language.",
      +  "enum": [
      +    "fr",
      +    "de",
      +    "it",
      +    "es",
      +    "ja",
      +    "pt",
      +    "zh",
      +    "ar",
      +    "nl",
      +    "el",
      +    "tr",
      +    "ko",
      +    "sv",
      +    "vi",
      +    "th",
      +    "id"
      +  ],
      +  "type": "string"
      +}
  2. Changed1 schema field changed
    • addedInput schema / properties / lookup / examples
      Added value: +[
      +  "Anthropic"
      +]
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

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 genuinely non-schema behavior: a $0.25 USDC x402 payment requirement and the presence of 'data confidence notes' on the results — the cost disclosure is especially important for an agent deciding whether to call. It doesn't say what happens for an unknown/private company or how partial data is signaled.

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 sentence front-loads the resource and the returned fields, followed by a short use-case clause and a cost clause — no filler. The field enumeration is a long run-on list, but it earns its place because there is no output schema to convey what comes back.

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?

With no output schema, the description must convey return content, and it does so thoroughly, plus it flags cost and confidence notes. Remaining gap is edge-case behavior (company not found, ambiguous names, private vs. public distinction) given the openWorld annotation.

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%: both `lookup` (company name, with an example) and `language` (enum with default and note that pricing is uniform) are fully documented in the schema. The description adds nothing about parameters, so the baseline 3 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 opens with a specific resource ('Private company deal intelligence') and enumerates the exact data returned: funding rounds, valuation, investors, revenue estimate, growth, headcount, deals/exits, comparables, industry, founding year, HQ. That field list distinguishes it from generic siblings like interzoid_business_info or interzoid_company_verification. It stops short of naming a sibling to explicitly differentiate from.

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?

It names concrete use contexts — venture capital, private equity, M&A research, investor prospecting — which tells an agent when this tool is the right pick. It gives no exclusions or 'use X instead when...' routing against the many related Interzoid entity tools, so the guidance is clear but incomplete.

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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