Zapmail 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 generates examples but doesn't describe how it behaves—e.g., whether it produces code snippets, markdown, or other formats; if it's a read-only operation; what permissions might be needed; or any rate limits. For a tool with no annotations, this lack of detail is a significant gap, leaving the agent with minimal behavioral insight.

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, efficient sentence: 'Generate practical examples for API endpoint usage with custom parameters.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence contributes directly to understanding the tool's function.

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 (3 parameters, no output schema, and no annotations), the description is incomplete. It lacks details on behavioral traits, output format, and usage context. While the schema covers parameters well, the description fails to compensate for missing annotations and output information, making it inadequate for full contextual understanding.

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 input schema has 100% description coverage, with clear documentation for all three parameters. The description adds minimal value beyond the schema, as it only mentions 'custom parameters' without elaborating on their purpose or usage. Since the schema already provides robust details, the baseline score of 3 is appropriate, reflecting that the description doesn't enhance parameter understanding but doesn't detract either.

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: 'Generate practical examples for API endpoint usage with custom parameters.' It specifies the verb ('Generate'), resource ('practical examples'), and scope ('API endpoint usage'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_api_scenarios' or 'search_api_endpoints', which might also relate to API examples or endpoints, so it falls short of a perfect score.

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 doesn't mention any prerequisites, context, or exclusions, such as when to choose this over 'get_api_scenarios' or 'search_api_endpoints'. Without such information, users must infer usage based on the purpose alone, which is insufficient for optimal tool selection.

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