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

With no annotations, the description carries the transparency burden and does well: it discloses the 1-credit cost, that empty results and failures are not charged, and the 24-hour cache behavior. It does not mention rate limits or auth, but the disclosed billing and caching behaviors are meaningful beyond the schema.

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 tight, front-loaded sentences: the first states what the tool returns, and the next two cover cost and caching. No wasted words or repetition of schema content.

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 simple two-parameter read tool with no output schema, the description provides enough: what fields are returned, what it costs, when failures are free, and how caching works. There is no missing information that would prevent an agent from calling it correctly.

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 100%, so the schema already explains both the url and cache parameters. The description reinforces the cache behavior but does not add new semantic meaning beyond what the parameter descriptions already provide, matching the baseline.

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?

States a specific verb ('Get'), a precise resource ('a LinkedIn post'), and the exact returned fields ('text, author, reactions, and comments count as structured JSON'). This clearly differentiates it from siblings like linkedin_post_transcript or linkedin_search_posts without needing to open their schemas.

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 usage context by requiring a specific post URL and explaining when to use cache=true versus the default fresh fetch. It does not explicitly name alternatives or exclusion conditions, but the context is clear enough for an agent to know this is the single-post details endpoint.

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