ffmiCompute the Fat-Free Mass Index (FFMI) and its height-adjusted form from weight and body fat (or lean mass), and flag whether it exceeds the ~25 natural ceiling.
| Name | Required | Description | Default |
|---|---|---|---|
| height | Yes | ||
| weight | Yes | ||
| methods | No | all | |
| body_fat | No | ||
| lean_mass | No |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes | ||
| consensus | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds context about flagging the natural ceiling (~25) and calculating height-adjusted form, providing extra behavioral insight beyond annotations.
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 a single concise sentence that front-loads the action and key output. It is efficient but slightly dense, missing some structural clarity.
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?
With an output schema present, the description does not need to cover return values. However, it omits explanation of the 'methods' parameter and the required input format (nested objects with units). The flag about natural ceiling is helpful but incomplete.
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?
Schema description coverage is 0%, so the description must compensate. It mentions weight, body fat, and lean mass but does not explain the nested structure of height and weight objects, nor the 'methods' parameter. The default 'all' for methods is not addressed.
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 computes FFMI and its height-adjusted form, with a specific verb and resource. It distinguishes from sibling tools like 'body-fat' or 'muscle-potential' by focusing on a unique metric.
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 use when weight and body fat (or lean mass) are available, but does not explicitly state when not to use it or provide alternatives. Usage context is clear but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct fitness metric or calculation method, e.g., TDEE via formula vs. data, body fat via different protocols, strength, muscle mass, etc. There is no overlap that would confuse an agent.
All tool names follow a consistent lowercase-with-hyphens pattern (e.g., adaptive-tdee, one-rep-max, powerlifting-attempts). The naming clearly conveys the purpose without mixing styles.
10 tools cover a comprehensive set of fitness calculations without being excessive. Each tool earns its place, and the number is well-scoped for the domain.
The tool surface covers major fitness estimation needs: TDEE (two methods), body fat, FFMI, macros, muscle potential, strength (1RM, attempts), and sarcopenia screening. No obvious gaps for calculation-oriented fitness tools.