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

Beyond annotations (readOnlyHint, idempotentHint), the description adds valuable context: the 12-hour high-resolution nature, bulk support via patient_ids, and a medical use caution. No contradiction with annotations.

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 short sentences, the first clearly stating the core purpose and the second adding bulk support. No redundant words; highly efficient.

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 simple tool (2 parameters, no output schema), the description covers the essential behavior and key constraints. Missing details like output format or error handling, but adequate for a read-only graph retrieval.

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 coverage, the description does not fully compensate. It mentions patient_ids for batched execution but does not explain the patient_id parameter or its required status. Some meaning is added, but incomplete.

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 specifically states it retrieves '~12h high-resolution glucose graph (graphData)', clearly identifying the resource and verb. It distinguishes from siblings like get_current_glucose or get_glucose_stats by emphasizing graph data and bulk support.

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 explicit guidance on when to use this tool versus alternatives. The description mentions it is for clinic/follower accounts and not for medical decisions, but does not compare to other glucose tools or provide when-not-to-use scenarios.

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