get_glucose_readings

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

The description discloses the window filtering behavior ('we fetch from start_minutes back and filter to the window') and the constraint start_minutes > end_minutes. With no annotations, this carries the full burden.

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?

Structured with Args, Examples, Note; each sentence adds value. The organization is clear and front-loaded with the purpose.

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 no output schema, the description covers input behavior well, but omits return value format. Still sufficient for selection and invocation.

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?

Every parameter gets meaning: minutes range, start/end semantics, max_count limit, and data's purpose. The schema has zero descriptions, so this fully compensates.

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 'Get historical glucose readings,' a specific verb+resource that clearly distinguishes this tool from siblings like get_current_glucose and get_statistics.

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 examples provide usage contexts (e.g., last hour vs time windows), but there is no explicit when-to-use vs alternatives. The historical vs current distinction is implicit.

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