get_event_stats

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

No annotations are present, so the description carries the burden. It discloses a performance characteristic ('Uses the API facets for fast, accurate counts') and a prerequisite (list_filters). However, it does not cover error conditions, authentication, or response structure, though the latter is likely covered by the output schema.

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 two sentences: the first front-loads the purpose, the second adds usage guidance and an efficiency note. No wasted words.

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?

With only two optional parameters and an output schema provided, the description adequately covers purpose, a key dependency, and implementation detail. It does not need to explain return values because the output schema exists. Complete for its complexity.

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 adds 'Use list_filters first' (already echoed in the schema) and implies filter categories, but adds marginal value beyond the structured parameter descriptions.

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 tool's function: 'Get statistics about events' with specific dimensions ('counts by format, topic, product, region, etc.'). This distinguishes it from siblings: search_events (lists events), get_event_details (single event), and list_filters (returns filter categories).

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 provides direct usage context: 'Use list_filters first to discover valid filter values' and notes the efficiency of 'single API call'. It lacks explicit when-not-to-use guidance compared to alternatives, but the context is clear and actionable.

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