Alko MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds valuable behavioral context beyond annotations by disclosing that 'results are cached', which is not covered by the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint). This informs the agent about performance and data freshness considerations. No contradictions with annotations exist.

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 front-loaded with the core purpose, followed by usage details and return values, all in three concise sentences. Each sentence earns its place by providing essential information without redundancy, making it efficient and well-structured.

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 moderate complexity, lack of output schema, and rich annotations, the description is mostly complete. It covers purpose, usage, return values, and caching behavior. However, it could improve by detailing output structure (e.g., format of 'wine details') or error handling, though annotations help mitigate some gaps.

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?

With 100% schema description coverage, the input schema already fully documents the three parameters (wineName, winery, vivinoUrl). The description adds minimal semantic value by mentioning search methods but does not elaborate on parameter interactions or usage beyond what the schema provides, aligning with the baseline for high 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 clearly states the tool's purpose with specific verbs ('look up', 'search') and resources ('wine ratings from Vivino.com'). It distinguishes itself from siblings by focusing on wine ratings rather than availability, products, recommendations, or store operations, making its unique function immediately apparent.

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 on when to use this tool by specifying search methods ('by wine name/winery or provide direct URL'). However, it does not explicitly state when not to use it or name alternatives among siblings, such as using 'search_products' for broader product searches instead of Vivino-specific ratings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.