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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely new context: the app-scoped id namespace constraint, the ready-to-use mention token format, and the paid-plan gating. It stops short of describing pagination or default result size.

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, each carrying distinct information: scope, output shape/id namespace, and gating requirement. No filler, and the core purpose is front-loaded.

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, the description usefully compensates by describing what each entry carries (person id plus @{urn:li:person:ID|Name} token) and the error condition. Only pagination/default-size behavior is left implicit.

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% and both parameters (q, limit) are fully documented in the schema, so the baseline is 3. The description adds no syntax or behavioral detail about the name filter or the 100-item cap beyond what the schema provides.

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 precise verb+resource ('List LinkedIn people captured from engagement on your connected company pages') and scopes the source of the data, which distinguishes it from sibling list tools like list_connections and list_posts. An agent knows exactly what population this returns.

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?

It makes the use case clear (building mentions) and discloses a concrete prerequisite — a paid plan, with the exact 403 UPGRADE_REQUIRED failure mode. It does not, however, name an alternative tool or say when not to use this one.

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