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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds a genuine behavioral constraint beyond that: the ownership requirement that silently fails for third-party posts. It omits any note on rate limits, latency, or data freshness.

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?

Two tight sentences, front-loaded with the capability and then the constraint. Every clause carries information; nothing is padded.

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, enumerating the returned metrics in the description is valuable and largely compensates. The main remaining gap is that the demographics breakdown is only implied by the parameter name, but the schema already explains it, so the definition is nearly 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 100%, and the schema fully documents both the accepted post identifier formats and the include_demographics flag. The description adds no parameter-level detail, so the baseline 3 is appropriate.

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 (Returns) plus resource (engagement metrics for one of your own LinkedIn posts) and enumerates the exact metric set, which cleanly distinguishes it from siblings like linkedin_get_post_comments, linkedin_get_post_reactions, and linkedin_get_my_engagement.

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?

Clearly bounds when the tool applies: only posts authored by the connected account, with an explicit exclusion ('analytics for other users' posts are not available'). It does not name an alternative tool for the excluded case, so it stops short of full routing guidance.

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