mfp_get_report

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the tool returns daily values and summary statistics, and clarifies the response_format parameter (markdown or json). However, it does not disclose any additional behaviors such as pagination, range limits, or error conditions. Given the annotations, a 3 is appropriate—it adds some value but does not go beyond what annotations already imply.

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 moderately concise: it leads with the core purpose, then provides a structured parameter breakdown and a return type note. It avoids fluff and each sentence contributes. The numbering and bullet-like format make it scannable. It could be slightly more succinct, but it is not excessively verbose.

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 (date range, nutrient selection, response format), the description covers the main aspects: what it does, parameters, and return type. However, it omits the date format (YYYY-MM-DD) which is present in the schema but not highlighted in the description—significant given low schema coverage. It also does not mention potential limitations like maximum date range or behavior when no data exists. Overall it is adequate but has gaps.

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 schema description coverage is reported as 0%, so the description must compensate. It explicitly lists all parameters (report_name, start_date, end_date, response_format) with types and defaults, and provides concrete examples for report_name ('Net Calories', 'Protein'). It also states the response_format values. While it does not include the date format pattern (which is in the schema), the description covers essentials well enough for an agent to call the tool correctly.

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 a nutrition report over a date range' and specifies it returns 'daily values for the specified nutrient/metric'. This is a specific verb+resource construction that distinguishes it from sibling tools like mfp_get_diary (which likely returns raw diary entries) and mfp_get_measurements (body metrics). The phrase 'analyzing trends and patterns' adds 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 gives only a vague use case ('Useful for analyzing trends and patterns in nutrition intake') but does not explicitly state when to use this tool over alternatives, nor does it mention when not to use it. It provides no comparison with sibling tools like mfp_get_diary or mfp_get_goals, leaving the agent to infer selection criteria from the purpose alone.

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