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

The description explicitly discloses that the tool sends data to the catalogue team, a mutation. It adds a key behavioral requirement beyond annotations: the message must be the user's own words (implicitly discouraged from paraphrasing or editing). This is useful guardrail behavior that isn't captured in the annotations, which are sparse (readOnly=false, destructive=false).

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 sentences no filler. First sentence tells what the tool does, second adds the most important usage constraint (consent), third clarifies the content requirement. It is front-loaded with purpose and ends with a crisp rule. Someone could trim little, but it earns each word.

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 feedback tool with full parameter descriptions and no complex output, the description provides enough context: it states the audience, the allowed feedback types, the consent guardrail, and verbatim content rule. It doesn't explain what happens after sending (e.g., acknowledgment) but that's not necessary for agent invocation. It covers the necessary parts.

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 100%, so all parameters are already documented. The description adds value by linking the conceptual 'feedback content' to message and kind, using examples (wrong-feeling-ish, missing brief, praise). However, it doesn't add new semantics beyond what the schema already provides for ref, brief, or kind. Meets the baseline for a fully described schema.

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 starts with a clear verb and resource ('Send the catalogue team feedback') and gives concrete examples of what feedback looks like (wrong-feeling page, brief that found nothing, praise). This distinguishes it cleanly from sibling tools like stye_search_tracks or stye_get_track, making the purpose immediately obvious.

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 gives strong context for when to use the tool: any time results feel wrong or a brief found nothing. It also states a critical when-not condition: only send with explicit user consent, and only after asking first. While it doesn't name alternative tools, none exist for this function; the consent rule acts as an explicit exclusion condition.

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