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 describes the tool as a listing operation with filtering capabilities, which implies read-only behavior, but does not address authentication requirements (beyond parameter listing), rate limits, pagination, or error handling. The mention of 'default: 100, max: 500' for 'top' hints at result limits, but overall behavioral context is minimal.

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 a detailed parameter breakdown. Every sentence earns its place, but the 'Args' section is lengthy due to the high parameter count, which is necessary given the lack of schema descriptions. It could be more front-loaded with key usage notes, but overall it is efficient.

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 tool with 10 parameters, 0% schema coverage, no annotations, but an output schema, the description is reasonably complete. It covers all parameters in detail and states the tool's purpose, though it lacks behavioral context like authentication flow or error handling. The presence of an output schema reduces the need to describe return values, making this adequate but not exhaustive.

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 fully compensates by providing detailed parameter semantics in the 'Args' section. It explains each of the 10 parameters, including purposes (e.g., 'Filter by department'), examples (e.g., 'DC55'), defaults (e.g., 'default: open'), and constraints (e.g., 'max: 500'), adding 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 verbs ('List job requisitions') and resources ('job requisitions with status and hiring manager'), and distinguishes it from siblings by focusing on requisitions rather than employees, permissions, or other HR data. The second sentence elaborates on the scope ('open or all job requisitions for tracking the hiring pipeline'), making it unambiguous.

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 ('for tracking the hiring pipeline') but does not explicitly state when to use this tool versus alternatives like 'get_candidate_pipeline' or 'search_employees'. It provides no guidance on prerequisites or exclusions, leaving the agent to infer based on the tool name and parameters.

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