get_glucose_stats

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

Annotations already declare readOnlyHint=true, so the description doesn't need to emphasize safety. It adds that the tool computes statistical metrics, which is useful but not a deep behavioral disclosure. No contradictions.

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?

Two sentences precisely conveying purpose and usage. No wasted words or redundancy. Information is front-loaded.

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?

Tool has one optional parameter, no output schema. Description explains what metrics are computed (avg glucose, GMI, time-in-range, variability), which compensates for missing output schema. Adequately complete for a statistical aggregation tool.

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?

There is one parameter (days) with 100% schema description coverage. The tool description does not repeat parameter details, but the schema already explains days, default, and data availability. Baseline score applies as schema does the work.

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?

Description clearly states it calculates comprehensive glucose statistics (average glucose, GMI, time-in-range, variability). This distinguishes it from siblings like get_current_glucose (single reading), get_glucose_history (raw data), and get_glucose_trends (trends).

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?

Description says 'Essential for diabetes management insights and identifying areas for improvement,' which provides clear context for when to use this tool. No explicit when-not or alternatives, but the purpose is clear enough.

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