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people_search

Search Apollo's database to find business contacts and leads using criteria like job titles, company domains, locations, and seniority levels.

Instructions

    Search for people/contacts in Apollo's database.

    This is Apollo's core prospecting tool - use it to find leads matching specific criteria.

    Args:
        q_keywords: Keywords to search for (e.g., "sales director")
        person_titles: Job titles to filter by (e.g., ["CEO", "CTO", "VP Sales"])
        person_seniorities: Seniority levels (e.g., ["c_suite", "vp", "director", "manager"])
        organization_domains: Company domains to search (e.g., ["google.com", "meta.com"])
        organization_locations: Company HQ locations (e.g., ["California, US", "New York, US"])
        organization_num_employees_ranges: Employee count ranges (e.g., ["1,10", "11,50", "51,200"])
        person_locations: Where person is located (e.g., ["San Francisco, CA"])
        contact_email_status: Email verification status (e.g., ["verified", "likely_to_engage"])
        page: Page number (default 1)
        per_page: Results per page (default 25, max 100)

    Returns:
        List of matching people with contact information

    Example:
        Search for VPs of Sales at tech companies in California:
        people_search(
            person_titles=["VP Sales", "Vice President of Sales"],
            organization_locations=["California, US"],
            organization_num_employees_ranges=["51,200", "201,500"]
        )
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
q_keywordsNo
person_titlesNo
person_senioritiesNo
organization_domainsNo
organization_locationsNo
organization_num_employees_rangesNo
person_locationsNo
contact_email_statusNo
pageNo
per_pageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's function as a search/prospecting operation, includes pagination behavior (page/per_page parameters with defaults), and provides a concrete example of usage. However, it doesn't mention rate limits, authentication requirements, or potential data freshness considerations.

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 well-structured with clear sections: purpose statement, usage context, parameter documentation, return value, and example. While comprehensive, it's appropriately sized for a 10-parameter tool. The front-loaded purpose statement is clear, though the parameter section is necessarily lengthy.

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?

Given the tool's complexity (10 parameters, no annotations, but has output schema), the description is quite complete. It covers purpose, usage context, detailed parameter semantics, return value format, and includes a helpful example. The main gap is the lack of behavioral constraints like rate limits or authentication requirements, which would be valuable for a search tool.

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

Parameters5/5

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

With 0% schema description coverage and 10 parameters, the description compensates excellently by providing detailed parameter documentation in the Args section. Each parameter includes clear explanations with examples (e.g., 'person_titles: Job titles to filter by (e.g., ["CEO", "CTO", "VP Sales"])'), which adds substantial value beyond the bare 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 purpose: 'Search for people/contacts in Apollo's database' with the specific verb 'search' and resource 'people/contacts'. It further distinguishes this as 'Apollo's core prospecting tool' which differentiates it from sibling tools like contacts_search, people_enrich, or organization_search by emphasizing its lead-finding function.

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 provides clear context about when to use this tool: 'use it to find leads matching specific criteria' and positions it as 'Apollo's core prospecting tool'. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the many sibling tools (e.g., when to use contacts_search vs. people_search).

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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