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

Annotations already declare this a safe, idempotent, closed-world read, so the bar is lower, and the description still adds behavior that structured fields cannot carry: the isPlaceholder flag signals the profile was never filled in, and it prescribes telling the user and pointing them at the app instead of quoting numbers. That is a genuine data-quality trap disclosed up front.

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?

Three sentences, front-loaded with purpose before the usage trigger and the placeholder caveat. Every sentence carries distinct information, and the repeated 'MALAI:' branding prefix is the only negligible padding.

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?

An output schema exists and the input schema is empty, so the description needn't explain return shape or parameters. What an agent actually needs - what the tool is for, when to call it, and how to handle the unfilled-profile edge case - is all present.

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 tool takes no parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The description adds no parameter-level detail, but none is needed - it correctly spends its words on the return semantics instead.

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?

States a specific verb and resource ('Read the user's body profile in MALAI') and enumerates exactly what comes back: age, sex, height, weight, activity level, goal, units. That field list distinguishes it cleanly from siblings like malai_get_nutrition_targets or malai_get_food_log, which return different data.

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?

Gives an explicit trigger condition: 'Use before advice that depends on their body or goal.' That is real when-to-use guidance tied to downstream intent. It stops short of naming an alternative tool or a when-not-to-call condition, but for a zero-param read of a distinct resource, the routing signal is clear enough.

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