Retrieve logged meals, macros, calories, hydration, and supplements for a client over a date range. Use it to analyze nutrition intake and track dietary trends.
Meals logged, macros, calories, hydration, supplements.
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | No | ||
| client_id | Yes | ||
| start_date | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 behavioral burden, yet it says nothing about read-only vs mutating behavior, authorization requirements, pagination, or how much data is returned. The content list is useful scoping but not behavioral disclosure.
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?
Seven words with no structure or front-loading; this is under-specification rather than conciseness, since the terse fragment leaves the core operation unstated.
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 so return values need not be described, but for a parameterized, annotated-less query tool the description still omits the required parameter, the date-range semantics, and any usage context, leaving it well short of complete.
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% for three parameters (client_id, start_date, end_date) and the description adds no meaning: it never mentions the required client_id or that start/end dates bound the query, so it fails to compensate for the gap.
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 name gives a specific verb+resource (get_nutrition_data) and the description enumerates the content domains covered (meals, macros, calories, hydration, supplements), which implicitly separates it from the sleep/exercise/cognitive siblings. However, the description itself is a bare noun phrase with no verb, so the actual purpose is only inferred from the tool name rather than stated.
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?
There is no when-to-use guidance, no mention of when to prefer this over get_lifestyle_summary or get_trends, and no indication of prerequisites or date-range expectations despite the tool’s optional start/end date parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.