linkedin_people_search

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

No annotations are provided, so the description carries the full burden. It says nothing about authentication/session prerequisites, rate limits, pagination behavior, or what results look like, offering only the connection-degree filter hint.

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?

A single short sentence, front-loaded with the core action and no wasted words. It is efficient, though perhaps overly terse given the gaps elsewhere.

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?

With no annotations, no output schema, and 0% parameter coverage, the description is too thin for a 4-parameter search tool. Pagination, result format, and auth requirements are all unspecified, leaving an agent without the context needed to call it well.

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 coverage is 0%, so the description should compensate but only loosely gestures at two of four parameters ('palabras clave' for keywords, 'grado de contacto' for connectionDegree). It never explains page/limit pagination semantics or the enum values 1/2/3 for connectionDegree.

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?

States a specific verb and resource ('Busca personas') and names the primary input dimension ('por palabras clave'). The resource 'people' implicitly distinguishes it from linkedin_jobs_search, but there is no explicit sibling differentiation.

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?

No guidance on when to use this tool versus alternatives (e.g., linkedin_jobs_search) or when not to. The connection-degree reference describes a capability, not a usage context, so the agent is left to infer applicability.

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