SF-MCP

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

With no annotations provided, the description carries full burden. It discloses that authentication credentials are required (auth_user_id, auth_password) which is crucial behavioral context. However, it doesn't mention rate limits, pagination, error handling, or whether this is a read-only operation (though 'View' implies reading). The description adds some value but leaves gaps in behavioral disclosure.

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 details, then parameter explanations. It's appropriately sized for a 7-parameter tool with authentication requirements. Minor improvement could be front-loading the authentication requirement more prominently, but overall it's efficient with minimal waste.

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 complexity (7 parameters, authentication, compensation option) and presence of an output schema (which handles return values), the description is quite complete. It covers purpose, usage context, and all parameter semantics. The main gap is lack of behavioral details like rate limits or error handling, but with an output schema, the description doesn't need to explain return values.

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 clear semantic explanations for all 7 parameters. Each parameter gets a meaningful description that explains what it represents (e.g., 'SAP data center code', 'Environment type', 'If True, also fetches salary history'), adding 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 with specific verbs ('View', 'Shows') and resources ('employee's job history', 'chronological job records'). It distinguishes this tool from siblings like 'get_employee_profile' or 'get_compensation_details' by focusing specifically on historical job changes rather than current data or compensation details.

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 about when to use this tool ('Useful for reviewing career progression'), but doesn't explicitly state when NOT to use it or mention specific alternatives. It doesn't compare against siblings like 'get_employee_profile' (current data) or 'get_compensation_details' (compensation focus), though the compensation parameter hints at overlap.

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