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hunt_person

Investigate a person's public footprint by searching LinkedIn, job roles, mentions, and news. Provide a name and optional context to receive a summary of profiles and public mentions.

Instructions

Investiga a presença pública de uma pessoa (LinkedIn, cargos, menções e notícias).

Args: name: Nome completo da pessoa. context: Contexto adicional (empresa onde trabalha, cidade, cargo, etc.).

Returns: Resumo de perfis e menções públicas encontradas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
contextNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries the full burden and does reveal that the tool scans public sources and returns a summary of profiles and mentions. It does not, however, disclose limits on result freshness, potential inaccuracies, or any access-related behavior, which would matter for correct interpretation of results.

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 compact and front-loaded: a one-sentence summary leads, followed by concise Args and Returns sections. Every sentence adds useful information, with no filler.

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?

Considering the simple two-parameter schema and the presence of an output schema, the description supplies enough to invoke the tool correctly: it states the exact inputs and the shape of the outcome. It stops short of being complete because it offers no guidance on choosing this tool among the five siblings, but that gap is shared with the usage-guidelines dimension.

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?

Schema coverage is 0%, so the description must add all parameter meaning, and it does: 'name' is clearly specified as Nome completo da pessoa and 'context' is explained with concrete examples (empresa, cidade, cargo). This fully compensates for the absent schema descriptions.

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 uses a specific verb ('Investiga') with a clear resource ('presença pública de uma pessoa') and enumerates concrete data sources (LinkedIn, cargos, menções e notícias). This makes the tool's purpose immediately clear and distinguishes it from siblings like hunt_company, which targets organizations.

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 intended use is implied by the tool's purpose — it should be used for investigating a person's public presence. However, it does not explicitly say when to prefer this over hunt_company, hunter_search, or extract_contacts, and gives no exclusions or alternative conditions.

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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