rsmiEstimate the appendicular skeletal muscle index (RSMI) from a DXA value (direct) and/or an anthropometric estimate (Wen 2011), and flag low muscle mass against EWGSOP2, AWGS, and Baumgartner sarcopenia cutoffs.
| Name | Required | Description | Default |
|---|---|---|---|
| age | Yes | ||
| sex | Yes | ||
| asm_kg | No | ||
| height | Yes | ||
| weight | Yes | ||
| methods | No | all |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes | ||
| skipped | Yes | ||
| consensus | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, indicating safe, non-destructive use. The description adds value by specifying the estimation sources (DXA/anthropometric) and cutoff criteria, providing behavioral context beyond the 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, somewhat long sentence that packs all key information. It is front-loaded with the purpose and estimation sources. No redundant phrases, but breaking into multiple sentences could improve readability slightly.
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 complexity (6 parameters, nested objects, multiple estimation methods, and multiple cutoffs), the description covers the main aspects. It mentions the two estimation methods and the three cutoffs. The presence of an output schema means return values do not need explanation. It does not clarify behavior when both estimation methods are provided, which is a minor gap.
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 explains that 'asm_kg' is the DXA value and the anthropometric estimate uses the other parameters (sex, height, weight, age). The 'methods' parameter is mentioned only indirectly. This adds meaningful context, though explicit enumeration of methods values would improve clarity.
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 estimates RSMI from DXA or anthropometric estimate (Wen 2011), and flags against specific sarcopenia cutoffs (EWGSOP2, AWGS, Baumgartner). This distinguishes it from sibling tools like body-fat or ffmi, which target different aspects of body composition.
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 for muscle mass assessment and sarcopenia screening, providing clear context. However, it does not explicitly state when not to use or name alternative tools; the sibling list and tool name make it clear this is specific to RSMI and sarcopenia.
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.