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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds that results are 'normalized events sorted by date,' providing useful behavioral context beyond the annotations. No contradictions found.

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 concise, information-dense sentences: the purpose is front-loaded, and every phrase adds value without redundancy. No filler or repetition.

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 list operation with strong annotations and fully documented parameters, the description covers the essential behavior: what it lists, optional filters, and return format ('normalized events sorted by date'). It lacks explicit output field details or pagination explanation, but the limit parameter and normalization note are sufficient for this simplicity level.

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 the baseline is 3. The description reinforces existing parameter semantics (keyword matches title/venue/genre/artist, date window) but does not add new parameter-level details beyond what the schema already provides. Thus, it earns the baseline.

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 opens with a specific verb and resource: 'List upcoming electronic/dance music events for a 19hz region.' This clearly distinguishes it from sibling tools like regions or recent_changes, making the tool's 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 conveys the core use case—listing upcoming events for a region—and mentions optional keyword and date filters, implying when to use it. It does not explicitly state exclusions or alternatives, but the context is clear enough for an agent to select it without confusion.

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