Find nutrition facts by searching Open Food Facts and USDA databases. Retrieve detailed food data for any query, with optional source filtering and pagination controls.
Search external food databases (Open Food Facts + USDA) for nutrition data
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number for pagination (default: 1) | |
| query | Yes | Search query (e.g., "chicken breast", "coca cola") | |
| source | No | Limit to a specific source (default: OFF) |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does disclose that this searches third-party external services and returns nutrition data, but it omits network/latency implications, pagination behavior, source defaults, result limits, and potential failure modes. This is minimal and non-contradictory, but not deeply transparent.
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 one concise, front-loaded sentence with no filler. It states the action first, then the specific external databases and the intended data type, so every word contributes to tool understanding.
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 simple read-only search tool with three well-documented parameters, the operation is adequately conveyed and the parameters are fully covered by the schema. However, with no output schema and no annotations, the description does not clarify what the returned nutrition data looks like or how this search relates to barcode-based and community-based alternatives, leaving meaningful gaps.
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 100%, so the baseline is 3 even though the description itself adds no parameter-specific guidance. The prose adds marginal value by expanding the source enum values (OFF/USDA into Open Food Facts + USDA) and clarifying that nutrition data is the target, but query and page semantics are already fully documented in the schema.
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 pairs a specific verb ('search') with a specific resource ('external food databases') and names the exact providers (Open Food Facts + USDA) plus the purpose ('nutrition data'). This distinguishes it well from siblings like search_community_foods (external vs community) and list_food_definitions (external vs local), even without inspecting the schema.
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 conveys clear general context: use this when you need nutrition data from external food databases. However, it does not explicitly state when not to use it, nor does it point to alternatives such as lookup_barcode or search_community_foods, so the routing guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.