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scalably-io

Hunter MCP

by scalably-io

create_lead

Add a new lead to Hunter using an email address, with optional contact details, list assignments, and custom attributes.

Instructions

Create one Hunter lead from a required email and optional current lead fields, list placement, and custom attributes. This is a single-attempt mutation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYes
notesNo
sourceNo
companyNo
twitterNo
websiteNo
positionNo
last_nameNo
first_nameNo
company_sizeNo
country_codeNo
linkedin_urlNo
phone_numberNo
leads_list_idNo
leads_list_idsNo
leads_list_nameNo
company_industryNo
confidence_scoreNo
custom_attributesNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

The annotations already signal a write operation (readOnlyHint=false), and the description adds the useful behavioral trait that this is a 'single-attempt mutation,' implying no automatic retry. It does not detail error handling, authentication needs, or side effects, but given the annotation coverage this is meaningful added context.

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 short sentences with no filler; the primary action and required input are front-loaded, and the 'single-attempt mutation' caveat earns its place as an important behavioral signal.

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

Completeness2/5

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

For a 19-parameter mutation with no output schema, this description is incomplete. It does not describe the return value, error behavior, duplicate handling, or how list placement fields interact, so an agent cannot fully anticipate the outcome of invoking it.

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?

With zero schema description coverage and 19 parameters, the description carries the burden of explaining fields, but only groups them into vague categories like 'current lead fields' and 'list placement.' It does not explain individual parameters, relationships such as leads_list_id vs leads_list_ids, or custom_attributes structure.

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 names a specific verb and resource: 'Create one Hunter lead' from an email plus optional fields. This clearly distinguishes it from the sibling read/enrichment tools like list_leads and email_finder, which are not mutations.

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 states that the tool is for creating a lead and identifies the required input (email) and optional categories, giving clear context for when to call it. It does not explicitly list exclusions or alternative tools, but no sibling tool performs lead creation, so the intended use is clear.

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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