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. It mentions authentication requirements (auth_user_id, auth_password) and a max limit for user_ids (20), which adds useful context. However, it lacks critical details: whether this is a read-only operation, potential rate limits, error conditions, or what the output schema contains. For a tool with sensitive compensation data and no annotations, this is a significant gap.

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 and appropriately sized. The first sentence states the purpose clearly, followed by a bullet-like 'Args:' section that efficiently documents parameters. Every sentence earns its place, with no redundant information. It could be slightly more front-loaded by integrating key constraints (e.g., max 20 IDs) into the purpose statement, but overall it's concise and effective.

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, sensitive data, no annotations) and the presence of an output schema, the description is moderately complete. It thoroughly documents parameters but lacks behavioral context (e.g., security implications, error handling). The output schema mitigates the need to explain return values, but for a compensation tool with authentication, more guidance on usage and risks would improve completeness. It's adequate but has clear gaps.

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?

Schema description coverage is 0%, so the description must compensate fully. It provides clear semantics for all 7 parameters: explaining what each represents (e.g., 'Employee user ID(s)', 'SAP data center code'), giving examples (e.g., 'DC55'), noting constraints ('max 20'), and specifying defaults ('Defaults to latest'). This adds substantial value beyond the bare schema. A 5 is reserved for exceptional detail like format specifics or interdependencies.

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: 'Get compensation breakdown for employees including base pay and pay components.' It specifies the verb ('Get'), resource ('compensation breakdown'), and scope ('for employees'), distinguishing it from sibling tools like get_employee_profile or get_employee_history. However, it doesn't explicitly differentiate from all siblings (e.g., query_odata might also retrieve compensation data), so it's not a perfect 5.

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 lists parameters but doesn't mention prerequisites, exclusions, or comparisons to sibling tools like get_employee_profile (which might include compensation) or query_odata (a generic query tool). Without such context, users must infer usage from the tool name and parameters alone.

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