get_statistics

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

Annotations already declare this as a safe, read-only, idempotent operation. The description adds that it returns 'historic summary statistics,' implying aggregation, but does not clarify what statistics are computed (e.g., mean, median) or how pagination via max_rows works.

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 a single short sentence, which is concise but omits vital detail. It is front-loaded with the core purpose but lacks necessary precision for a tool with 9 parameters.

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?

Despite having an output schema, the description does not explain what statistical metrics are returned or how the 'kind' parameter alters the query. The tool has 9 parameters and two required fields; the one-sentence description is insufficient for effective use.

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?

With 0% schema description coverage and no parameter information in the tool description, the agent must rely solely on parameter names. Critical parameters like 'kind' (enum of period_of_record or date_range) and 'computation_type' remain unexplained, making it difficult to construct correct inputs.

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 retrieves 'historical summary statistics' for specific locations, which distinguishes it from sibling tools that retrieve raw observations or current values. However, it does not mention the 'kind' parameter (period_of_record vs date_range) which is essential for understanding the two modes.

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?

No guidance is provided on when to use this tool versus alternatives like get_observations or get_latest_values. The description does not specify use cases, prerequisites, or exclude scenarios.

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