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

Annotations already cover the read-only and open-world profile, yet the description adds real operational context: the data is scraped from the public page rather than the gated /posts/ tab, the result set is capped near ten items, `hasMore` is always false, featured member posts attribute the member as author, and each call costs 1 credit. That is unusually rich disclosure for a tool whose annotations are minimal.

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?

Purpose is front-loaded in the first sentence, followed by source constraints, the result cap, the hasMore caveat, author attribution, and cost — every sentence carries a distinct, actionable fact with no filler.

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 does the work of explaining what comes back (posts with reaction and comment counts, author attribution, hasMore flag) and what it costs. The only meaningful gap is the silent `cache_max_age` parameter, which an agent must guess at.

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 only 50%: `url` is documented in the schema, but `cache_max_age` is undocumented in both places, and the description never addresses it. The description reinforces that the URL points at a company page, but it does not compensate for the undocumented caching parameter, leaving half the input surface unexplained.

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 concrete verb and resource: 'Recent posts from a company page, with reaction and comment counts.' That is enough to separate it from linkedin_post (single post) and linkedin_company (page metadata). It never explicitly names those siblings, so the differentiation is inferable rather than stated.

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 usage context is implied by the scope notes ('caps the result at roughly the last ten posts', 'no logged-out pagination'), which tell an agent when this tool is a dead end for deep history. However, there is no explicit routing to alternatives such as linkedin_searchPosts or linkedin_post, and no stated prerequisites for the URL.

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