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

Annotations already note the tool is not read-only, not idempotent, and open-world, yet the description adds valuable behavioral context: it is free and consumes no credits, and it implies an async request (submitting to a team). This goes beyond the schema and annotations by explaining the practical implications of using the tool, though it does not detail any response or follow-up process.

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?

The description is concise—three sentences that cover purpose, usage condition, and content guidance. It is front-loaded with the core action, followed by when to use it, and ends with practical tips. No filler; every sentence earns its place. Structure is ideal for quick comprehension.

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?

Given the tool's simplicity (two parameters, no output schema, no nested objects), the description covers the essential context: what it does, when to use it, and what to include. It also notes it's free. While it doesn't mention potential response time or what happens after submission, that's not critical for calling the tool correctly, so the description is sufficiently 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?

The input schema already covers both parameters (summary and details) with clear descriptions, so the baseline is 3. The description adds further guidance on the 'details' field—emphasizing to include the user's goal and why current tools are insufficient—which is more specific than the schema's generic description. This extra clarification improves the quality of requests without being redundant.

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?

The description clearly states the action: 'Ask the Hermoso team for a capability that doesn't exist yet.' It specifies the resource (a missing capability) and verb (request), and the examples (unsupported platform, missing model, export format) distinguish it from the many operational sibling tools. An agent can immediately tell this is for requesting new functionality, not executing existing operations.

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 description explicitly says when to use it: 'Use this when you need something Hermoso genuinely can't do' and gives concrete examples. It also instructs the user to describe the use case ('Say what the user was trying to achieve, not just the feature name'). This effectively routes the agent to use this tool only when no existing tool can complete the task, and clarifies the expected content of the request.

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