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

Annotations already flag destructiveHint and idempotency, but the description adds the state machine it operates over (sent, failed, cancelled, in-flight), the refusal code like_not_cancellable with a reason, and the not-found case like_not_found. That is real behavioral context beyond structured fields.

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 sentences with no filler; the primary action and its guarantee are front-loaded, followed by the two failure modes in a logical order.

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 one-parameter cancellation tool with annotations present and an output schema covering return shape, the description supplies everything an agent needs: success semantics, refusal semantics, and the recommended user-facing response on failure.

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 single post_urn parameter is documented there as the value returned by like_post. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 and resource ('Cancel a like before it is sent') with an explicit scope constraint ('so it never reaches LinkedIn'), which cleanly separates it from the sibling like_post that creates likes. Nothing about the intent is ambiguous.

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?

Gives clear conditions under which the call succeeds versus fails, and prescribes the right agent behavior on failure ('tell the user it can no longer be cancelled rather than retrying'). It stops short of naming a sibling alternative for creating/cancelling other like states, so it is strong context without explicit alternative routing.

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