SF-MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions authentication requirements and result limits ('default: 50, max: 200'), it doesn't describe important behavioral aspects like rate limits, error handling, response format, pagination, or whether this is a read-only operation. For an 11-parameter search tool with authentication, this leaves significant gaps.

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 purpose first, then usage context, followed by detailed parameter documentation. While comprehensive, the parameter section is quite lengthy for 11 parameters, making it somewhat dense. However, every sentence serves a clear purpose, and the information is appropriately front-loaded.

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 (11 parameters, authentication, search functionality) and the presence of an output schema, the description is partially complete. It thoroughly documents parameters but lacks behavioral context about the search operation itself. The output schema existence means it doesn't need to explain return values, but other behavioral aspects remain undocumented.

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 fully compensates by providing detailed parameter documentation in the 'Args:' section. It explains what each parameter does, provides examples ('e.g., 'DC55', 'DC10', 'DC4''), specifies defaults, and clarifies usage ('searches first name and last name', 'direct reports'). This adds substantial value beyond the bare schema.

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: 'Search for employees by name, department, location, or manager.' It specifies the verb ('search') and resource ('employees'), and distinguishes itself from siblings by focusing on flexible search capabilities rather than retrieving specific employee data like 'get_employee_profile' or 'get_employee_history'.

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: 'Find employees without knowing their exact user IDs.' It implies this is for discovery rather than direct lookup, but doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, which prevents a perfect score.

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