ZOOQ - LinkedIn Data for AI Agents

email_find

Read-onlyIdempotent

Discover a person's work email from their first name, last name, and company domain. Returns the address plus a confidence score. (Costs 10 Zooq credits.)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "first_name": "<first_name>",
      "last_name": "<last_name>",
      "domain": "<domain>"
    },
    "name": "email_find"
  }
}

Input Schema

Name	Required	Description
`domain`	Yes	Company domain as a bare hostname — no scheme, no @, must contain a dot.
`last_name`	Yes	The person's last name.
`first_name`	Yes	The person's first name.

Output Schema

Name	Required	Description
`email`	No	Example value was a string
`found`	No	Example value was a boolean
`catch_all`	No	Example value was a boolean
`confidence`	No	Example value was a string

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 1, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds the cost (10 Zooq credits) and the confidence score output, which are valuable behavioral details beyond annotations. No contradiction found.

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

Conciseness5/5

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

Two sentences, zero fluff. The purpose is front-loaded, and the cost note is appended in a parenthetical. Every word earns its place.

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?

For a simple 3-parameter lookup tool with annotations covering safety and an output schema present, the description is complete. It specifies the purpose, inputs, output (including confidence score), and a key operational constraint (cost). Nothing an agent needs to decide to call it is missing.

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%, so all three parameters are already documented in the schema with their own descriptions. The tool description adds no extra parameter meaning beyond restating the inputs, which meets but does not exceed the baseline for full coverage.

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 states a clear verb ('Discover'), a specific resource ('a person's work email'), and the exact required inputs (first name, last name, company domain). It also mentions the output (address plus confidence score), which distinguishes it from sibling tools like email_reverse or email_find_by_profile.

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 when you have the three identity components, but it does not explicitly mention when to prefer this over siblings (e.g., email_find_by_profile, email_prospects). No 'when not to use' or alternative guidance is provided, leaving the agent to infer.

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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