Coffee Company MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool queries status, implying a read-only operation, but doesn't specify authentication needs, rate limits, error conditions, or what the query returns beyond the high-level purpose. For a tool with zero annotation coverage, this is insufficient to inform the agent about operational behavior.

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 core purpose stated first. The additional lines for the HTTP API and parameter are brief and relevant. However, the inclusion of the HTTP API endpoint might be extraneous for an AI agent focused on tool invocation rather than implementation details.

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 complexity (simple query with 1 parameter), the presence of an output schema reduces the need to describe return values in the description. However, with no annotations and minimal behavioral context, the description is adequate but lacks depth. It covers the basic purpose and parameter semantics but misses usage guidelines and detailed behavioral traits, making it minimally viable.

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 description adds meaningful semantics beyond the input schema. The schema only defines 'order_id' as a required string with no description. The description explains that 'order_id' is the '权益订单号' (equity order number), clarifying its purpose in the context of equity issuance. With 0% schema description coverage and 1 parameter, this compensates well, though it could provide more detail on format or 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: '查询权益发放状态（电子券是否发放成功）' translates to 'Query equity issuance status (whether electronic coupons have been successfully issued).' This specifies the verb (query) and resource (equity issuance status/electronic coupons). However, it doesn't explicitly differentiate from sibling tools like 'equity_detail' or 'coupon_query,' which might have overlapping functionality.

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 no guidance on when to use this tool versus alternatives. It mentions the corresponding HTTP API endpoint but doesn't indicate prerequisites, scenarios for use, or comparisons to sibling tools like 'equity_detail' or 'coupon_query.' This leaves the agent without context for tool selection.

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