Query employee records for complete details like address, contact, employment dates, cost center, and employment type. Use this read-only tool to retrieve accurate HR and payroll information.
Query employees with full detail: address, contact, employment dates, cost center, employment type. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | ||
| take | No | ||
| order | No | GraphQL order clause | |
| where | No | GraphQL where filter |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It explicitly states 'Read-only', which tells the agent there are no side effects, and it lists the data scope ('full detail: address, contact, employment dates, cost center, employment type'). It does not mention rate limits or response shape, but for a simple query tool this is acceptable.
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 a single front-loaded sentence with no filler. Every part contributes either to identifying the resource, specifying the returned fields, or signaling safety ('Read-only').
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 read-only query with four optional parameters and no output schema, the description covers the essential return fields and the non-mutating nature. The schema handles pagination and filtering mechanics. A more complete description might include GraphQL clause syntax examples or response structure, but the definition is largely sufficient for correct invocation.
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?
The description adds no parameter-level detail; it only describes the returned employee fields. The schema covers 'order' and 'where' with descriptions and 'skip'/'take' with defaults, so an agent can invoke the tool safely with defaults. With 50% schema description coverage and no parameter explanation in the description, there is a clear gap, but the conventional parameter names and optionality make it minimally viable.
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 uses a specific verb ('Query') and resource ('employees') and enumerates the exact fields returned: address, contact, employment dates, cost center, employment type. It clearly distinguishes this query tool from the many mutation-oriented siblings in the list. The 'Read-only' label further reinforces its scope.
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 gives clear context: use this tool when you need detailed employee data. The 'Read-only' marker also signals it is a safe retrieval operation rather than a mutation. It does not name alternatives or explicit exclusions, but no dedicated employee-query sibling exists, so the guidance is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.