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. It effectively describes the tool's behavior: it returns audit history including who, when, and what changes, with filtering capabilities and pagination (top parameter). It mentions authentication requirements and default/max values for 'top,' though it doesn't cover error handling, rate limits, or data freshness.

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, followed by return details, usage context, and a clear parameter list. It's appropriately sized for a 10-parameter tool, though the 'Args:' section is lengthy but necessary. Every sentence earns its place, but some redundancy exists (e.g., 'optional' is stated multiple times).

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?

For a complex tool with 10 parameters, 0% schema coverage, no annotations, but with an output schema, the description is largely complete. It covers purpose, behavior, and detailed parameter semantics. The output schema likely handles return values, so the description doesn't need to explain them. Minor gaps include lack of error cases or performance characteristics.

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?

Given 0% schema description coverage, the description compensates fully by providing detailed semantics for all 10 parameters. It explains each parameter's purpose (e.g., 'instance: The SuccessFactors instance/company ID'), format constraints (e.g., ISO format for dates), optionality, defaults (top default 100, max 500), and relationships (role_name as alternative to role_id). This adds significant 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 verb ('Get modification history') and resource ('RBP roles'), distinguishing it from sibling tools like 'get_rbp_roles' (which likely lists roles) and 'get_role_assignment_history' (which likely tracks user assignments). The second sentence elaborates on what information is returned, reinforcing the audit-focused purpose.

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 implies usage context through 'This helps audit role configuration changes over time,' suggesting it's for auditing purposes. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_rbp_roles' or 'get_role_assignment_history,' nor does it mention prerequisites or exclusions beyond the required authentication parameters.

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