linkedin_my_profile

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It is exceptionally transparent: it explains that LinkedIn defers certain sections until scrolling and that this server does not scroll, so those sections are usually absent and reported as UNKNOWN, not zero. It also admits the profile-strength meter is not exposed and that derived data is labelled as such.

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 longer than average but every sentence adds information: it states the purpose, enumerates outputs, discloses limitations, and clarifies how to interpret absence. It is well-paragraphed and front-loads the core purpose before diving into nuance. No filler exists.

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?

For a read-only profile tool with an output schema, the description covers all necessary aspects: what is returned, the caveat about missing sections, how to interpret missing data, and a hint about the details_urls for further investigation. The 'include_skills' parameter behavior is also disclosed through the schema. Nothing an agent needs to call and interpret the tool correctly is omitted.

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?

There is a single parameter, include_skills, and its schema description is already very informative, explaining the effect (additional page load, pages_loaded: 2) and the trade-off. The description itself does not elaborate on the parameter, but because the schema coverage is 100% and the schema text is detailed, the parameter semantics are clear. A score of 4 reflects the extra value of the schema description beyond a bare type.

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 uses a specific verb and resource ('Read your own LinkedIn profile') and immediately lists the concrete output fields (name, headline, location, About text, sections). It clearly distinguishes itself from siblings by focusing on the user's own profile and explicitly notes what is not included (profile-strength meter).

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 explains when the tool is appropriate (reading your own profile) and provides guidance on handling missing sections by pointing to details_urls. It does not explicitly contrast with sibling tools, but the tool name and the content give enough context for correct selection. The explanation of the 'include_skills' parameter also adds usage context.

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