analyzeProduct
Get AI-powered nutritional analysis of any food product by providing its name or barcode.
Instructions
Get AI nutritional analysis of a product
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| nameOrBarcode | Yes |
Get AI-powered nutritional analysis of any food product by providing its name or barcode.
Get AI nutritional analysis of a product
| Name | Required | Description | Default |
|---|---|---|---|
| nameOrBarcode | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as whether the tool is read-only, requires authentication, or has rate limits. For an AI analysis tool, this is a significant omission.
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 very concise (one sentence), but it is under-specified. Conciseness should not come at the cost of missing essential information. The description fails to earn its place by not providing enough guidance.
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 lack of output schema, annotations, and the presence of many sibling tools, the description is woefully incomplete. It does not describe what the analysis returns, how to format the input, or when this tool is appropriate.
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 single parameter nameOrBarcode has no description coverage in the schema (0%). The tool description does not explain its format, examples, or constraints. The parameter semantics are entirely missing.
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 it provides 'AI nutritional analysis of a product', which is a specific purpose. However, it does not distinguish this from sibling tools like getNutriScore, which also provide nutritional assessments. The purpose is clear but lacks unique differentiation.
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?
No usage guidelines are provided. The description does not indicate when to use analyzeProduct vs. siblings like getNutriScore, getAllergenCheck, or searchProducts. There is no guidance on prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Jatin-IITB/openproductsfacts-mcp'
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