Calculates daily protein intake in grams from body weight and age using ICMR-NIN and PROT-AGE guidance, and returns the per-meal protein threshold for meal planning.
Daily protein target in grams for a given body weight and age, using ICMR-NIN and PROT-AGE guidance, plus the per-meal threshold.
| Name | Required | Description | Default |
|---|---|---|---|
| age | No | ||
| situation | No | e.g. training, dieting, pregnancy | |
| weight_kg | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it does disclose the standards applied (ICMR-NIN, PROT-AGE) and that a per-meal threshold is included in the result. However, it says nothing about how the optional 'situation' (training, dieting, pregnancy) alters the target, nor what happens when it is omitted, nor about determinism or units for age.
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?
A single front-loaded sentence with no filler. Slightly terse for the amount of behavior it leaves unexplained, but every clause earns its place.
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?
No output schema, no annotations, and low parameter coverage: an agent cannot know the result's structure, whether the per-meal threshold is a separate field, or how 'situation' affects the number. For a three-parameter domain calculator this is under-specified.
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 only 33% (only 'situation' is described, and only by example), so the description must compensate. It gives meaning to weight_kg and age by framing the output as grams per body weight and age, but it completely omits the 'situation' input, which would materially change the computed target.
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 computation: 'Daily protein target in grams for a given body weight and age', and adds the per-meal threshold and the guidance sources. This clearly separates it from food-lookup siblings like lookup_food and compare_foods, though it never names them.
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?
Usage is only implied by the purpose statement – an agent can infer this is the tool for computing a target rather than inspecting foods or costs. There is no explicit when-to-use, when-not, or mention of how it relates to siblings such as protein_cost or search_guides.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.