search_foodsPer 100 g nutrition for the foods foodose uses, each with a realistic serving size and a GLP-1 tolerance rating describing how well it tends to sit when appetite is low. Free to use with attribution.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | Matches the food name, category or tags. | |
| tolerance | No | How well the food tends to sit on a GLP-1. | |
| minProteinPer100g | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the core safety profile is covered. The description adds meaningful behavioral context beyond annotations by specifying the per-100g normalization, realistic serving size, and the meaning of the GLP-1 tolerance rating, while its 'foods foodose uses' phrasing aligns with openWorldHint=false.
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 compact and front-loads the most important datum ('Per 100 g nutrition') before describing serving size and tolerance. The licensing sentence 'Free to use with attribution' is extra but brief; overall every part is useful and there is no redundant filler.
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?
With no output schema, the description does enough by explaining what fields to expect: nutrition per 100g, serving size, and GLP-1 tolerance rating. Annotations cover the read-only/idempotent behavior, and the schema covers query/tolerance plus limit boundaries, so an agent can invoke the tool without critical missing context.
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 descriptions cover query and tolerance, but limit and minProteinPer100g lack descriptions. The description adds value by clarifying tolerance semantics and explaining that nutrition is per 100g, which helps interpret minProteinPer100g, but it does not fully compensate for the undocumented parameters, so it is minimally adequate.
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 title supplies the explicit verb+resource ('Search the foodose food database'), and the description clarifies that the tool returns per-100g nutrition, serving sizes, and GLP-1 tolerance ratings for foods. This distinguishes it from search_recipes, though the description itself is a noun phrase rather than a direct action statement.
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 this is the tool for looking up food-level nutrition and GLP-1 tolerance data, especially versus search_recipes. However, it does not explicitly state when to use this tool instead of get_appetite_ceiling or calculate_glp1_target, nor does it offer any exclusion criteria.
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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