LibreLink MCP Server

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

The description adds context beyond annotations: it mentions the standard range (70-180 mg/dL) and the role of healthcare providers, which helps set expectations. The annotations provide 'destructiveHint: true,' indicating a mutation operation, and the description aligns with this by implying customization (a write action). No contradiction exists, and the description enhances understanding of the tool's impact.

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 front-loaded with the core purpose in the first sentence, followed by additional context in the second. Both sentences are necessary: the first defines the action, and the second provides medical context. There is no wasted text, making it efficient and well-structured.

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 (a mutation with two parameters) and the presence of annotations (destructiveHint) but no output schema, the description is reasonably complete. It explains the purpose and context, though it could benefit from more details on effects or error handling. However, it adequately covers the essentials for a configuration 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 add specific meaning to the parameters beyond what the input schema provides. The schema has 100% coverage with clear descriptions for 'target_low' and 'target_high,' including defaults and ranges. The description mentions the standard range but doesn't elaborate on parameter usage or constraints, so it meets the baseline for high schema coverage.

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: 'Customize your target glucose range for personalized time-in-range calculations.' It specifies the verb ('customize'), resource ('target glucose range'), and outcome ('personalized time-in-range calculations'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'configure_credentials' or 'get_glucose_stats', which slightly limits its clarity in context.

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 by mentioning 'your healthcare provider may recommend different targets,' suggesting it's for adjusting settings based on medical advice. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., no comparison to 'get_glucose_stats' for viewing current ranges or 'configure_credentials' for other settings). This leaves the usage context somewhat vague.

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