Get Company Employees

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

Annotations already indicate readOnlyHint and openWorldHint. The description adds important context: the demographics aggregate is unique to this tool, the 'company_name' must be an exact LinkedIn URL slug (with examples of mismatches), and the keywords filter restricts by name, title, or skill. This surpasses what annotations convey.

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 concise with five sentences, each carrying meaningful information. It is well-structured: main purpose, alternative usage, optional parameter details, slug requirement with example, and a fallback suggestion. No unnecessary text.

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 output schema exists (so return details are covered), annotations provide behavioral hints, and sibling tools are listed, the description covers all necessary context: what it does, how to use alternatives, parameter specifics, and how to resolve slug uncertainty. No gaps.

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 100%, baseline 3. The description adds value by explaining that 'company_name' is the exact slug (not display name) and provides examples, and clarifies that 'keywords' is an optional filter for name, title, or skill. This goes beyond the schema 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 lists employees and demographics from the LinkedIn /people/ page, specifying the types of demographics included. It differentiates itself from the sibling 'search_people' tool by mentioning that filtered search by network degree or location should use the alternative.

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 explicit guidance on when to use this tool versus alternatives: it recommends 'search_people' with current_company set for filtered searches by network degree or location, and advises using 'search_companies' first if uncertain about the company slug.

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