AgentFood — USDA Nutrition Intelligence
Server Details
USDA FoodData Central nutrition data — search 1M+ foods, get full nutrition profiles (macros, vitamins, minerals), and compare foods side-by-side. Public domain government data.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.8/5 across 3 of 3 tools scored.
Each tool has a clearly distinct purpose: search_food for finding foods by name, get_nutrition for retrieving full profiles by ID, and compare_foods for side-by-side comparisons. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (search_food, get_nutrition, compare_foods). The naming is uniform and predictable.
With 3 tools, the set is concise and well-scoped for a nutrition intelligence server. Each tool performs a necessary function without redundancy or excess.
The tools cover the core workflow of searching for foods, retrieving detailed nutrition, and comparing profiles. Missing features like filtered searches by nutrients or dietary filters, but the essential operations are present.
Available Tools
3 toolscompare_foodsAInspect
Compare nutrition profiles of multiple foods side-by-side. Identifies winners by protein and calorie density.
| Name | Required | Description | Default |
|---|---|---|---|
| ids | No | Comma-separated USDA FDC IDs (e.g. "173950,2187885,1103516") | 173950,2187885,1103516 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the input format (comma-separated USDA FDC IDs) and output focus (winners by protein and calorie density), but lacks details on limits, error handling, or whether it is read-only.
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?
Two concise, front-loaded sentences with no filler. Every sentence adds value: purpose and output feature.
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?
Given the simple tool with one parameter and no output schema, the description is fairly complete. It explains purpose and key output, though it could mention limitations like maximum number of foods or data freshness.
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 schema has 100% coverage, describing the single parameter 'ids' with format and default. The description adds no further semantic meaning beyond what the schema provides, so baseline score of 3 applies.
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 description clearly states the tool's purpose: compare nutrition profiles of multiple foods side-by-side and identify winners by protein and calorie density. This distinguishes it from siblings like get_nutrition (single food) and search_food (finding foods).
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 usage for comparing multiple foods but does not explicitly state when to use this tool versus alternatives like get_nutrition or search_food. No exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_nutritionAInspect
Get full nutrition profile for a specific food by USDA FDC ID. Returns macros, vitamins, and minerals.
| Name | Required | Description | Default |
|---|---|---|---|
| fdc_id | No | USDA FoodData Central ID (e.g. 173950 = avocado raw) | 173950 |
| format | No | abridged or full | abridged |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It mentions the return types (macros, vitamins, minerals) but lacks details on rate limits, idempotency, or data source freshness. Adequate but basic.
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 a single, efficient sentence that conveys the core functionality without redundancy.
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?
For a tool with two simple parameters and no output schema, the description sufficiently covers what the tool does and returns. Minor gap: no mention of error handling or data source, but overall complete for its simplicity.
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 coverage is 100%, so the description adds little beyond the schema's parameter descriptions. It reaffirms the tool's purpose but does not enhance parameter semantics.
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 description clearly states it retrieves a full nutrition profile using a USDA FDC ID and specifies return types (macros, vitamins, minerals), effectively distinguishing it from sibling tools like search_food and compare_foods.
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 usage when you have an FDC ID but does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. Usage is implied but not guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_foodAInspect
Search USDA FoodData Central for foods by name. Returns nutrition macros for matching foods.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Food name to search (e.g. "chicken breast", "avocado") | chicken breast |
| brand | No | Filter by brand owner | |
| limit | No | Number of results (max 25) | |
| dataType | No | Filter by data type: Foundation, SR Legacy, Survey (FNDDS), Branded |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses data source (USDA FoodData Central) and output type (nutrition macros) but omits details like rate limits, authentication, or handling of no results.
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?
Two concise, front-loaded sentences with no redundant information. Every sentence adds value.
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?
Given 4 parameters, no output schema, and no annotations, the description is adequate but minimal. It explains primary function but doesn't detail return structure or pagination beyond 'nutrition macros'.
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 coverage is 100% with clear descriptions for each parameter. The description adds minimal extra value (e.g., examples for 'q'), so baseline 3 is appropriate.
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?
Description clearly states verb 'Search' and resource 'USDA FoodData Central for foods', and distinguishes from siblings 'compare_foods' and 'get_nutrition' by specifying search vs. compare/get.
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?
Implies usage for food name search but lacks explicit guidance on when to use versus siblings or when not to use (e.g., if exact nutrient data is needed, use get_nutrition). No 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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