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Hunter

by io.github.pipeworx-io
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Email Finder

email_finder
Read-onlyIdempotent

Find the most likely professional/work email address for a specific person at a domain on Hunter.io. Returns the email, a confidence score, position, and the number of corroborating sources. Example: email_finder({ domain: "stripe.com", first_name: "Patrick", last_name: "Collison" })

Input Schema

NameRequiredDescriptionDefault
domainYesCompany domain, e.g. "stripe.com"
_apiKeyNoOptional — your own Hunter.io API key for higher limits; omit to use the shared Pipeworx key.
last_nameYesPerson's last name, e.g. "Collison"
first_nameYesPerson's first name, e.g. "Patrick"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "domain": "stripe.com",
+    "first_name": "Patrick",
+    "last_name": "Collison"
+  },
+  {
+    "domain": "apple.com",
+    "first_name": "Tim",
+    "last_name": "Cook"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds that it returns email, confidence score, position, and sources. No contradictions, but it could mention rate limits or API key dependency beyond schema.

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?

The description is concise, front-loaded with the action, and includes a helpful example. Every sentence adds value with no wasted words.

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 tool with 4 parameters and no output schema, the description covers the key aspects: purpose, return values, and an example. It is sufficient for an agent to use correctly.

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 coverage is 100% with clear parameter descriptions. The description adds an example showing parameter usage, but doesn't significantly enhance meaning beyond what's already in 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 clearly states the tool's action: finding the most likely professional email for a specific person at a domain on Hunter.io. It distinguishes from siblings like email_verifier (verifies) and domain_search (domain-level), making the purpose unambiguous.

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 implies usage when you have a person's name and domain, and provides an example. While it doesn't explicitly mention alternatives or when not to use, the context is clear enough for an agent to decide.

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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