body_comp_trend

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

With no annotations provided, the description carries full burden. It explains the data combined (weight, body fat, training volume, calorie balance) and default date ranges, but omits behavioral traits like destructive potential, authentication needs, or rate limits. It is adequate but not explicit.

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 concise: a summary sentence, a question, and an args list. It is front-loaded with the key purpose and contains no wasted words. Minor improvement could be more structured bullet points.

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 presence of an output schema (not shown), the description does not need to explain return values. It covers the tool's purpose, parameters, and default behavior. It is fairly complete for a trend analysis tool.

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 coverage is 0%, but the description fully explains both parameters in the Args section: format (YYYY-MM-DD) and defaults (90 days ago, today). This adds significant meaning beyond the bare schema.

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 it tracks body composition over time (weight, body fat, training volume, energy balance) and answers the specific question 'am I gaining muscle or fat?'. It uses a specific verb ('track') and distinguishes itself from sibling tools like get_weight_trend or get_workout_history.

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 when wanting to understand overall body composition trends, but does not explicitly state when not to use it or mention alternative tools. The guidance is implied rather than explicit.

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