search_label_ingredientsSearch the SKS nutrition ingredient library (largely USDA-based) for an ingredient's nutrients per 100 g, label declaration name and allergens. Each result says where its data comes from and which nutrients are missing.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Ingredient, e.g. 'wheat flour', 'cane sugar', 'whole milk powder'. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful context beyond that: the library is largely USDA-based, results include provenance, and missing nutrients are flagged. It does not discuss pagination or limits, but it meaningfully explains result trustworthiness.
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 sentences, front-loaded with the action and resource, then the return content. Every sentence contributes useful information with no wasted wording.
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 search tool with no output schema, the description adequately explains the result content and provenance. However, it omits limit semantics and when-to-use guidance relative to siblings, leaving meaningful gaps for an agent selecting and invoking the tool.
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 describes query with examples, but the description adds no parameter-level detail. The limit parameter, with its default of 5 and maximum of 15, is undocumented in both the description and schema, and schema coverage is only 50%, so the description does not compensate for the gap.
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 states a specific verb and resource: search the SKS nutrition ingredient library for an ingredient. It also specifies the returned content (nutrients per 100 g, label declaration name, allergens), but it does not explicitly differentiate this from siblings such as check_retailer_ingredients or calculate_nutrition_label.
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?
Usage is implied by the purpose: use this when you need ingredient-level nutrient, label-name, or allergen data. However, there is no explicit when-to-use guidance, no exclusions, and no routing to alternatives like the retailer ingredient checker or nutrition-label calculator.
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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