Search LinkedIn Posts

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

Annotations already state read-only, idempotent, and non-destructive behavior. The description adds valuable beyond-annotation context: 'Returns one cursor page while browser traversal remains privately bounded' and 'Names resolve only through exact visible choices' disclose pagination, traversal limits, and name-resolution limitations.

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?

Four compact sentences front-load the purpose and then add only operationally critical caveats (content type behavior, name resolution, cursor paging). There is no filler or repetition; every sentence earns its place.

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 large filter surface, the description covers the key behavioral constraints agents need to know: pagination returns one cursor page, name resolution requires exact visible choices, and content type follows LinkedIn's single-choice control. The output schema handles return-value details, so the description is sufficiently complete.

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 low (14%), and the description partially compensates by summarizing the filter categories and clarifying single-choice content type and exact-name matching. However, most parameter-level semantics are left to the schema; the description does not fully bridge the coverage gap.

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 ('Search') and clearly identifies the resource ('visible LinkedIn content'), enumerating many filter dimensions. It distinguishes itself from sibling search tools (jobs, people, companies) by targeting posts.

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 clearly implies use cases by listing available filters (From-member/company, posted-by, mentioning-member/company, author-industry/company, etc.), giving agents a strong sense of when to invoke it. It does not explicitly name alternatives, but the sibling tool names make those obvious.

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