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davidmosiah

Wellness Nourish

Estimate meal

nourish_estimate_meal
Read-onlyIdempotent

Estimate nutritional content from a brief meal text using local deterministic defaults. Provides confidence scores and handles unresolved items.

Instructions

Estimate nutrition for a short meal text using local deterministic defaults. Accepts text or meal_text; preserve unresolved and confidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoMeal text to estimate, for example 'pão de queijo, café preto, banana'.
localeNoen-US
meal_textNoAlias for text for agents that naturally call this parameter meal_text.
meal_typeNoother
response_formatNojson
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds context that the tool 'preserve[s] unresolved and confidence', indicating the output includes uncertainty metrics, and mentions 'deterministic defaults' assuring no external side effects. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two short sentences, no redundancy. It front-loads the core action. However, it could be slightly more structured (e.g., bullet points) but remains effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters (none required), no output schema, and moderate annotations, the description covers the primary purpose and a key behavioral trait (preserving unresolved/confidence). However, it omits details on output format, locale/meal_type effects, and error handling. While adequate, there are clear gaps for an agent to fully understand the tool without checking other sources.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 40%, and the description merely reiterates schema descriptions for text/meal_text ('Accepts text or meal_text'). It does not explain locale, meal_type, or response_format beyond their names. With low coverage, the description should compensate but fails to add meaningful semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Estimate' and resource 'nutrition for a short meal text', and adds specificity with 'using local deterministic defaults' and handling of unresolved items. This distinguishes it from sibling tools like nourish_estimate_meal_photo (photo input) and nourish_search_food (search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide any guidance on when to use this tool versus alternatives. It neither mentions exclusions nor suggests preferred scenarios. For example, it could contrast with photo estimation or barcode lookup, but it does not.

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

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