get_compensation_analytics

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

With no annotations, the description discloses the 5000-record limit for performance and the underlying query join (EmpCompensation + EmpJob), which is transparent. However, it does not mention authentication requirements (implied by auth parameters) or whether the operation is read-only, though the name suggests it.

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 concise with three sentences: first states purpose, second explains data source, third notes a performance limitation. It is front-loaded and contains no superfluous text.

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 existence of an output schema, the description does not need to detail return values. It covers the key behavioral context (5000-record limit, join, scope field options). However, it omits explanation of authentication parameters and the optional data_center/scope_value fields, which could be helpful for an agent to use the tool correctly.

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 coverage is low (20%). Only the scope_field parameter is described with allowed values in the description. Other parameters (data_center, scope_value, auth_user_id, auth_password) lack any semantic explanation beyond schema types, leaving the agent to infer their meaning. The description adds some value for scope_field but does not compensate for the overall low coverage.

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 it retrieves compensation statistics (average, min, max, median compa-ratio, range penetration) grouped by a scope field. It specifies the data source (EmpCompensation joined with EmpJob) and the scope_field parameter's allowed values, making the purpose distinct from sibling tools like get_headcount 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 does not explicitly guide when to use this tool versus alternatives. It mentions a 5000-record limit for performance but lacks context on when this tool is appropriate compared to other analytics queries. No exclusions or alternative tool references are provided.

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