mfp_get_measurements

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds that data is 'historical measurement data with dates and values,' but it does not disclose additional behavior like ordering, units, missing-data handling, or how response_format changes the output beyond the schema.

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 compact and front-loaded with the core operation, followed by a clear Args/Returns block. The 'Useful for tracking...' sentence is slightly extra but provides legitimate use-case context. Overall, it is efficient and easy to scan.

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?

For a simple read-only retrieval tool, the description plus annotations and output schema provide enough information to call the tool correctly: what it returns, the date-range semantics, parameter names/defaults, and output format options. It does not discuss error behavior or all possible measurement names, but those are not critical for basic invocation.

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?

Given the context signal of 0% schema description coverage, the description carries the burden of documenting parameters. It explicitly lists measurement, start_date, end_date, and response_format with defaults and value options. This compensates for the coverage gap, though it does not add edge-case semantics beyond what the schema already implies.

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 opens with a specific verb and resource: 'Get body measurements (weight, body fat, etc.) over a date range.' This clearly states what the tool does and distinguishes it from siblings like mfp_set_measurement and mfp_get_diary without requiring the reader to inspect the schema.

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 provides a clear use case: 'Useful for tracking weight loss progress and body composition changes.' This gives the agent contextual guidance on when to choose this tool. However, it does not explicitly mention alternatives or when not to use it, such as using mfp_set_measurement for writing measurements.

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