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

With no annotations, the description carries the behavioral burden and does disclose the key traits: the team reads every message, and an API key produces a reply via get_notifications. It stops short of covering anonymity guarantees, moderation, or rate limits, but the core follow-up behavior is communicated.

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 purpose and followed by the follow-up mechanism. No filler.

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 three-parameter feedback tool with rich schema descriptions and no output schema, the description covers purpose, audience, and what happens after submission. Minor gaps like whether feedback is anonymous are acceptable.

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 coverage is already 100%, so the baseline is 3. The description adds real value by explaining the outcome of supplying api_key — a reply arrives in get_notifications — which gives the parameter behavioral meaning beyond its schema text.

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 — telling the iamai.markets team how to improve the marketplace or reporting a bug. That clearly separates it from transactional siblings such as create_listing or get_notifications.

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 first sentence gives the two intended use cases (improvement suggestion and bug report). It does not state exclusions or contrast explicitly with other tools, but the context is clear enough to choose it correctly.

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