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

With no annotations provided, the description carries the burden of behavioral disclosure, and it meets it reasonably well by stating exactly what the tool returns: post content, engagement metrics, attached media, a repost flag, and optional sentiment. This is a read/search operation, so the absence of auth/rate-limit notes is less critical; the description conveys the observable behavior of the tool.

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 compact and front-loaded: the action, the query-or-filter requirement, the most useful filters, and the return payload are all stated in two sentences. Every clause adds usable information, with no filler or repetition of schema details.

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 an 11-parameter search tool with no output schema and no annotations, the description supplies the key missing context: what the tool searches, how filters work, and what the response contains. It does not mention pagination or the sentiment surcharge, but those are available in the input schema, so the overall package is strong but not exhaustive.

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?

The input schema already describes all 11 parameters with 100% coverage, so the baseline is 3. The description adds value beyond the schema by grouping parameters into 'powerful filters' and clarifying semantic distinctions such as posts BY vs posts that MENTION a company or person, which helps an agent choose the right filter for the intended search.

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 opens with a specific verb and resource: 'Search LinkedIn posts.' It goes on to list the distinct filter types (author, author_title, company, mentions, industry) and the returned fields, so an agent can unambiguously identify this as the post-search tool and distinguish it from siblings like search_linkedin_companies or linkedin_company_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?

The description gives clear operational guidance: provide a query and/or a filter, and explains how filters apply (e.g., author_title 'applies alongside a query'). It does not explicitly name alternative tools or exclusion criteria, but the usage context is sufficiently clear for selecting and invoking this tool.

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