Get B2B contact information for Weingut Dreissigacker. Returns structured contact data, importer info, and next steps for trade inquiries. B2B-Kontaktdaten für Gastronomie, Handel und Importeure.
| Name | Required | Description | Default |
|---|---|---|---|
| market | No | Target market or country, e.g. 'USA', 'UK', 'Japan', 'Deutschland' | |
| interest | No | Specific interest, e.g. 'wine list curation', 'import partnership', 'event wines' |
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, and non-destructive behavior. The description adds what the tool returns (contact data, importer info, next steps), complementing the structured metadata without contradiction.
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 and front-loaded with the main action, followed by a brief summary of return content. The German sentence is redundant but not wasteful, keeping the overall length appropriate.
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 tool's simplicity (2 optional parameters, no output schema), the description adequately summarizes return values and context. It lacks detailed return structure but is sufficient for expected use cases.
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 descriptions cover 100% of the two parameters, so the description does not need to add parameter semantics. It provides no extra detail beyond the schema, matching the baseline for high schema coverage.
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 uses a specific verb ('Get') and identifies a clear resource ('B2B contact information for Weingut Dreissigacker'). It also distinguishes from sibling tools by focusing on contact data rather than food pairing or wine recommendations.
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 clear context for when to use this tool—when B2B contact information, importer info, or next steps for trade inquiries are needed. It does not explicitly mention alternatives but the purpose is unambiguous enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.