get_daily_demand_statistics

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

No annotations are provided, but the description discloses it returns a JSON string with daily stats and summary. It does not mention authentication, rate limits, or side effects, but as a read-only tool, this is acceptable. The presence of an output schema reduces the need to describe return structure in detail.

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 well-structured with sections for purpose, arguments, returns, and examples. It is concise (no superfluous sentences) and front-loaded with the main action. Every sentence adds value.

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 (2 parameters, output schema present), the description covers all necessary context: what the tool does, parameter formats, return type, and usage examples. It is fully adequate for an agent to invoke it correctly.

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 0%, but the description fully compensates by specifying both parameters (start_date, end_date) with their format (YYYY-MM-DD). It adds meaning beyond the schema's raw type definitions, ensuring correct usage.

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 it retrieves daily demand statistics (max, min, sum) for a period, distinguishing it from siblings like analyze_demand_volatility or get_demand_summary. The verb 'Get' and resource 'daily demand statistics' are specific and unambiguous.

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?

While the description explains when to use a date range and includes examples, it does not explicitly compare itself to sibling tools or state when not to use it. The guidance is implicit from the tool name and functionality, but the dimension requires explicit differentiation.

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