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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable context beyond annotations: 'Read-only CGM data — not for medical decisions without clinician review', which is an important behavioral caveat.

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 three concise sentences: purpose, warning with alternatives, and bulk support note. Every sentence adds value with no redundancy.

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?

Covers most aspects: output fields, safety warning, alternatives, bulk usage. However, it does not differentiate from the sibling 'librelink_get_latest_reading' and omits explanation of the 'account' parameter.

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?

The input schema has 0% description coverage, so the description partially compensates by explaining that patient_ids enables bulk support, implying patient_id is for a single patient. However, the 'account' parameter is left unexplained.

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's purpose: 'Get the latest single glucose reading for a connection' with specific output fields (value, trend, color, isHigh/isLow flags). It also distinguishes from sibling tools by mentioning alternatives for multi-point history and stats.

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?

Explicitly provides when-to-use and when-not-to-use guidance: 'Use librelink_get_glucose_graph for multi-point history or librelink_get_glucose_stats for time-in-range.' Also mentions bulk support for batched execution.

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