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

With no annotations, the description carries the full burden, and it discloses real operational behavior: a flat 7-credit cost whether cached or not, and refund on failure. It also states the exclusive-or input constraint. It does not cover auth requirements or what a failure actually looks like, so it is strong but not complete.

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?

Three sentences, zero waste. The purpose and return shape come first, usage second, and the operational constraints (exclusive input, cost) last — a well front-loaded structure.

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 output schema and no annotations, the description compensates by describing the return shape ('a list of names and member counts') and the credit/refund model. The exclusivity rule for the identifier params is also covered. Missing auth/permission context keeps it from a 5.

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 100%, so baseline is 3. The description goes beyond the schema by stating 'Give exactly one of url or vanity_name or company_id' — the schema lists zero required parameters, so this exclusivity rule is information the agent cannot get from the structured fields alone.

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?

Specific verb + resource ('Fetch the counts on a company's People tab') followed by the exact facets returned (location, function, education, skills). The framing as aggregate counts distinguishes it from the sibling get_linkedin_company_people, which enumerates individuals, without needing to open either schema.

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?

States clear use cases: 'size a team, or to see where a company hires.' That gives an agent solid context for when this is the right call, but it names no alternative tool and gives no exclusions, so it stops short of full routing guidance.

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