SF-MCP

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. While it mentions authentication requirements and filtering parameters, it doesn't describe important behavioral aspects: whether this is a read-only operation, potential rate limits, pagination behavior beyond the 'top' parameter, error conditions, or what the output contains. For a tool with 10 parameters and authentication needs, this leaves significant gaps in understanding how the tool behaves.

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 well-structured with a clear purpose statement followed by organized parameter documentation. Each parameter explanation is brief and focused. While slightly longer due to the 10 parameters, every sentence serves a purpose. The structure helps users quickly understand both what the tool does and how to use it.

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 (10 parameters, authentication requirements) and the presence of an output schema, the description is moderately complete. It covers authentication needs and filtering parameters adequately, and the output schema will handle return value documentation. However, for a tool with no annotations and significant behavioral implications (tracking performance data across an organization), the description should provide more context about limitations, security considerations, or typical 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?

With 0% schema description coverage, the description compensates well by providing clear explanations for all 10 parameters. Each parameter gets a brief but meaningful explanation, including examples for 'data_center', default values, and filtering logic (e.g., 'applied client-side' for department/manager filters). The description adds substantial value beyond the bare schema, though it could provide more detail on parameter formats 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: 'Track performance review form completion across the organization.' This specifies the verb ('track') and resource ('performance review form completion') with organizational scope. However, it doesn't explicitly differentiate from sibling tools like 'get_employee_profile' or 'search_employees' that might also retrieve performance data, leaving some ambiguity about when this specific tool is uniquely appropriate.

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. With many sibling tools available (e.g., 'get_employee_profile', 'search_employees', 'query_odata'), there's no indication of whether this is the primary method for performance review data or if other tools might be better for specific scenarios. The description lacks any 'when-to-use' or 'when-not-to-use' context.

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