get_statistics

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

With no annotations provided, the description carries the full burden of disclosure. It explains window semantics (e.g., minutes ago) and includes defaults, but it does not explicitly state that the operation is read-only, what statistics are computed, or how low/high thresholds affect output. The behavior is partially transparent but lacks depth.

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-organized with an Args section and examples. It is concise, with no filler, and each sentence serves a purpose—whether defining a parameter or demonstrating usage. The Examples section adds practical value without bloat.

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 6 parameters and no output schema, the description doesn't explain what the returned statistics include (e.g., average, time-in-range, hypoglycemia counts) or how low/high thresholds influence the computation. This gap leaves an agent unsure whether the tool meets its exact needs. However, the examples and parameter details provide adequate basic context.

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%, and the description fully compensates by defining each parameter's range (1-1440 for minutes), units (mg/dL for thresholds), and semantic meaning (e.g., start_minutes as 'minutes ago from now'). Examples illustrate usage clearly. The only minor gap is the vague 'data' parameter, but overall parameter semantics are strong.

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 'Get glucose statistics for a time period', specifying a specific verb and resource. This distinguishes it from sibling tools like get_current_glucose and get_glucose_readings by focusing on aggregated statistics rather than individual or current readings.

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 clear context through parameter explanations (minutes, start_minutes, end_minutes) and examples showing different time windows. However, it does not explicitly mention when to prefer this over sibling tools or provide exclusions like 'use get_glucose_readings for raw data', so it falls short of a 5.

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