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

Annotations already declare this is a non-destructive, non-idempotent write, and the description adds the meaningful disclosure that a human (the founder) reads submissions. It does not say whether the submitter gets any response, tracking, or confirmation, which is the main behavioral unknown for a feedback tool.

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 short sentences with zero filler; the scope of acceptable content is front-loaded before the audience note. Every sentence carries information an agent can act on.

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 two-parameter, fully documented feedback tool with annotations covering the safety profile, this is nearly complete. The only missing piece is what happens after submission (acknowledgment, visibility of the suggestion).

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% – both 'text' and 'contact' are documented in the schema, including the note that text can be in any language. The description adds no further parameter-level detail, so 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 concrete verb+resource: submit a suggestion (missing capability, better data format) about the platform. It implicitly separates itself from question-answering siblings like ask_question and note-writing siblings like add_business_note, though it never names them explicitly.

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?

Usage is only implied ('anything that would make the platform more useful to AIs'), with no explicit when-to-use or when-not-to-use guidance and no mention of ask_question as the alternative for something that expects an answer.

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