calculate_body_composition

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

No annotations are provided, so the description carries the full burden. It covers side effects (read-only, stateless), authentication (none for basic, API key for pro), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency, and data privacy (no storage/logging). This is exceptionally thorough.

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 long but well-structured with clear sections (Args, Behavior, When to use, Behavioral Transparency). It front-loads the core purpose. While every sentence adds value, some repetition exists (e.g., read-only stated twice), but overall it's efficient.

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?

The tool has 9 parameters, 3 required, and no output schema. The description covers inputs and behavior thoroughly but does not describe the output format or list of calculations returned (e.g., BMI value, body fat percentage). Given the complexity, this is a notable 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 add meaning. It lists all 9 parameters with brief explanations and default values. For example, sex is described as 'male, female' and activity_level as 'sedentary, light, moderate, active, very_active', which is helpful but lacks further detail on units or constraints.

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 explicitly states the tool calculates BMI, body fat estimate, BMR, and TDEE, with a clear list of inputs. It distinguishes from sibling tools that focus on training plans, form checking, workouts, and calorie tracking, making the purpose unambiguous.

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 includes 'When to use' and 'When NOT to use' sections, giving context for appropriate usage (e.g., structured analysis, not for real-time production without review). However, it doesn't explicitly contrast with siblings, though the purpose is distinct enough.

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