linkedin_search_people

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 value by disclosing the return fields (names, headlines, locations, identifiers) and the downstream integration with other tools, going beyond the structured metadata.

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

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

The description is two sentences, front-loaded with the primary action, and every clause adds information: what it searches, what filters are available, what it returns, and how to follow up. No wasted words.

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

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

For a search tool with 11 parameters and no output schema, the description provides a solid high-level overview: filters, return data, and next steps. It does not mention pagination or limit specifics, but given the schema covers limit and the core usage is clear, it is sufficiently complete.

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

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

Schema description coverage is 55%, and the description compensates by listing the semantic families of filters (connection degree, current/past company, school, industry, location, job title) that map to the otherwise undocumented array parameters like schoolIds, industryIds, and pastCompanyIds. It does not detail every parameter (e.g., limit, firstName, lastName), but the schema covers those with descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb and resource: 'Search for people'. It enumerates the key filter dimensions (connection degree, company, school, industry, location, job title) and what it returns (names, headlines, locations, profile identifiers), making it distinct from sibling tools like linkedin_search_companies or linkedin_search_jobs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for people search and provides downstream guidance: 'Use the identifiers with linkedin_get_profile, linkedin_send_connection_request or linkedin_send_message.' This clarifies the workflow but does not explicitly contrast with alternatives or state when not to use it, which prevents a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.