Get the EU recall history of a brand: how many Safety Gate alerts it has on record, over what period, how many were classed as serious risk, the dominant hazard types, product categories and countries of origin. Useful for supplier and counterparty risk screening.
| Name | Required | Description | Default |
|---|---|---|---|
| brand | Yes | Brand or manufacturer name. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It does this well by summarizing the output content (count, period, serious risk count, hazard types, product categories, countries of origin), implying a read-only operation and giving the agent a clear sense of what to expect. It does not mention any rate limits or data freshness, but for a simple retrieval tool this is adequate.
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 concise, two sentences, with the action and resource front-loaded. Every word adds value, from the specific output details to the use case, with no redundant or filler content.
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, the description is remarkably complete. It explains what data will be returned (counts, categories, origins) and suggests when to use it, making it fully self-contained for an agent deciding to invoke it.
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%, and the parameter 'brand' is already described as 'Brand or manufacturer name.' The tool description reiterates the parameter's role ('history of a brand') without adding new details such as format, length limits, or examples. Thus it meets the baseline for high schema coverage but does not exceed it.
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 function: 'Get the EU recall history of a brand'. It specifies the resource (brand) and the action (get history), and distinguishes itself from siblings like check_product_recall (likely product-level) and list_recent_recalls (likely recent alerts) by focusing on brand-level EU recall history with aggregated statistics.
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 provides a clear use case: 'Useful for supplier and counterparty risk screening', indicating when this tool is appropriate. However, it does not explicitly mention when not to use it or recommend alternatives, so it lacks explicit exclusions.
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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