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

The annotations only declare the safety profile (readOnly=false, destructive=false, idempotent=false, openWorld=false); the description adds real behavioural detail: a 1000-character limit, a ban on links/code/contact details/secrets, and that bugs are verified against 'our own records and re-runs' rather than a report alone. These are meaningful constraints beyond structured data, though it doesn't say what a submission returns.

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?

It is a dense single sentence plus a closing pointer, but the enumeration of types and the constraints are front-loaded and every clause carries actionable content. Slightly long for what an agent needs, but no filler sentences.

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 8-parameter mutation with a nested competitor object and no output schema, the description covers the type taxonomy, per-type requirements, content limits, and where to read the reply (my_feedback). Combined with full schema coverage and annotations, an agent has enough to call it correctly; only the absence of explicit sibling differentiation leaves a minor gap.

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 all eight parameters are already documented, including order_id being required for type bug and would_pay_cents being wish-only. The description largely restates these schema semantics, adding cross-tool context only for prompt_id (tied to whoami), so baseline 3 is right.

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 (send feedback) and enumerates the message kinds it accepts (wish, pain_point, competitor, improvement, bug, praise), which an agent can map directly onto the required 'type' enum. It also names where the answer appears (my_feedback), distinguishing it from a pure write.

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 per-type conditions: wish needs would_pay_cents, bug needs order_id, an answer to whoami needs prompt_id, and it says to check my_feedback for the reply. However, it never distinguishes itself from close siblings such as make_wish, review, or vote_roadmap, so the routing is clear but not exclusionary.

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