search_people

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool searches LinkedIn but doesn't mention limitations (e.g., rate limits, authentication needs, result format, pagination, or whether it's read-only). For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded, starting with the core purpose followed by parameter details. The 'Args' section is structured clearly, though it could be more integrated into the flow. There's minimal waste, with every sentence adding value.

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?

Given the tool's moderate complexity (2 parameters, no annotations, but an output schema exists), the description is partially complete. It covers the purpose and parameters adequately, but lacks behavioral context (e.g., search scope, limitations). The presence of an output schema reduces the need to explain return values, but more operational details would improve completeness.

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?

The description adds meaningful semantics beyond the schema, which has 0% coverage. It explains that 'keywords' are search terms with examples like 'product manager', and 'location' is an optional filter with examples like 'London'. This compensates well for the schema's lack of descriptions, though it doesn't detail constraints like character limits.

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 as 'Search for people on LinkedIn' with a specific verb ('Search') and resource ('people on LinkedIn'). It distinguishes from siblings like 'search_jobs' by specifying the resource type, though it doesn't explicitly contrast with 'get_person_profile' which retrieves individual profiles rather than searching.

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 provides no guidance on when to use this tool versus alternatives like 'get_person_profile' (for retrieving a specific person's details) or 'search_jobs' (for job searches). It lacks context about use cases, prerequisites, or exclusions, offering only basic functional information.

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