LibreLink MCP Server

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

The description adds behavioral context beyond annotations by specifying the types of statistics calculated (e.g., GMI, time-in-range percentages) and their purpose for diabetes management. Annotations provide readOnlyHint=true, indicating a safe read operation, but the description enhances this with insights into data usage. It does not contradict annotations, as 'calculate' aligns with read-only analysis.

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 appropriately sized and front-loaded, with two concise sentences that directly state the tool's function and its value. Every sentence earns its place by defining purpose and utility without redundancy or unnecessary elaboration.

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 tool's complexity (statistical analysis with one parameter) and annotations (readOnlyHint), the description is mostly complete, explaining what is calculated and why. However, without an output schema, it could benefit from more detail on return values or data formats, though the purpose is well-covered for a read-only 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?

The description does not mention the 'days' parameter or add meaning beyond the input schema, which has 100% coverage and fully documents the parameter. With high schema coverage, the baseline score is 3, as the description provides no additional parameter details, but it doesn't need to compensate for gaps.

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 with specific verbs ('calculate comprehensive glucose statistics') and resources ('glucose statistics'), listing key metrics like average glucose, GMI, time-in-range percentages, and variability metrics. It distinguishes itself from sibling tools like 'get_current_glucose' or 'get_glucose_history' by focusing on aggregated statistical analysis rather than raw data retrieval.

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 implies usage context ('essential for diabetes management insights and identifying areas for improvement'), suggesting it's for analytical purposes. However, it does not explicitly state when to use this tool versus alternatives like 'get_glucose_trends' or 'get_glucose_history', nor does it provide exclusions or prerequisites for use.

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