lookup_barcode
Lookup a food product by EAN/UPC barcode.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| barcode | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| found | No | ||
| barcode | No | ||
| message | No |
Lookup a food product by EAN/UPC barcode.
| Name | Required | Description | Default |
|---|---|---|---|
| barcode | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| found | No | ||
| barcode | No | ||
| message | No |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "barcode": {
+ "type": "string"
+ },
+ "found": {
+ "type": "boolean"
+ },
+ "message": {
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering the safety profile. The description adds that the lookup is for food products via barcode but does not disclose behaviors like not-found handling or data source limitations. Since annotations handle primary safety traits, a mid-range score is appropriate.
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 concise sentence that front-loads the action ('Lookup') and target ('food product'), with no wasted words or 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?
Given the simple single-parameter nature and the presence of an output schema plus read-only annotations, the description is complete enough. It defines the input scope and purpose without needing to explain return values since the output schema covers that.
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 provides no description for the 'barcode' parameter (0% coverage), so the description must compensate. It does so by specifying the barcode format as EAN/UPC, which gives the agent meaningful input expectations beyond the parameter name alone. This is valuable but lacks detail on exact format constraints.
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 with a specific verb 'lookup' and a well-defined resource 'food product' plus a specific key type 'EAN/UPC barcode'. This distinguishes it from sibling tools like search_foods, which would search by text, making the purpose unambiguous.
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?
There is no guidance on when to use this tool versus alternatives such as search_foods. The description only states what it does, not the appropriate context for using it or when to prefer another tool.
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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