Look up calorie information for a food or meal.
Accepts natural-language descriptions including quantity and unit, e.g. "2 large eggs", "8 oz salmon", "1 cup rice", "3 slices bacon", or a plain food name like "banana". Returns the matched food, its calories, the total for the amount given, and how it was calculated.
Free tier: 100 calls/day. Beyond that, pay $0.005 USDC per call (x402).
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description discloses rate limits (100 calls/day) and payment model, as well as what the tool returns (matched food, calories, total, calculation). This is sufficient behavioral context.
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?
Five sentences, front-loaded with purpose, clear structure. Could be slightly more concise, but no extraneous information. Effective and well-organized.
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 single-parameter tool with no output schema or siblings, the description covers purpose, usage examples, behavioral traits, and cost. Complete and adequate for agent understanding.
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?
Only one parameter 'query' with no schema description, but the tool description thoroughly explains its use: accepts natural-language descriptions with examples. This adds significant meaning beyond the bare schema type.
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 it looks up calorie information for a food or meal, with a specific verb and resource. It distinguishes itself by accepting natural-language descriptions, which is unique and clear.
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?
Provides examples of natural-language queries and mentions the free tier and payment model. No sibling tools exist, so no alternative guidance needed, but it gives enough context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clearly defined.
With a single tool, naming is trivially consistent. The name 'lookup_calories' follows a clear verb_noun pattern.
A single tool is at the low end for a server. While it covers the core functionality, a calorie database typically benefits from additional tools like barcode scanning or batch lookups. The count feels slightly thin.
The tool handles natural-language calorie lookups adequately but lacks support for other common nutritional information (e.g., macros), batch queries, or logging capabilities. Notable gaps exist for a comprehensive nutrition service.