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

The annotations already declare read-only, idempotent, open-world, non-destructive behavior, so the bar is lower. The description adds a real behavioral detail beyond them: a second company fetch happens by default, driven by the most recent experience entry with a company URL. It doesn't cover auth or rate-limit characteristics, which keeps it from a 5.

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, front-loaded with the operation and return surface, then the use case, then the sibling routing. No filler and nothing buried.

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 only two parameters, no output schema, and an annotated read-only profile, the description is complete: it enumerates the returned fields, explains the default side-fetch, and covers retrieval. An agent can call it correctly without further inference.

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%, so both parameters are already fully documented with examples, and the description adds little beyond restating the identifier forms. The one extra signal is the default-on company lookup, which is also in the schema default.

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 gives a specific verb and resource ('Get one person's LinkedIn profile') and enumerates the returned fields (name, headline, positions, education, counts), so it cannot be mistaken for the company or post tools. It also names the two nearest siblings it is not.

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 states a concrete use case ('research a prospect or a candidate, for example before you contact them') and explicitly routes agents elsewhere: linkedin_search_people to find a person first, linkedin_bulk_get_profiles for 2 to 10 profiles. When-to-use and alternatives are both spelled out.

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