Retrieve employee records to resolve names from receipt IDs. Filter by employee UUIDs, paginate results, and identify waiters, cashiers, and staff.
List employees (waiters, cashiers, staff). Use to resolve employee names from IDs found in receipts.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Results per page (1-250) | |
| cursor | No | Pagination cursor from previous response | |
| employee_ids | No | Comma-separated employee UUIDs to filter |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already establishes this is a safe read. The description adds that results map IDs to names, which hints at return content, but says nothing about pagination behavior, default page size, or whether the employee_ids filter is required. With annotations covering safety, this is modest added value.
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?
Two short sentences, zero filler. The resource is named first and the use case follows immediately.
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 simple read-only list tool with full schema documentation and no output schema, the description covers purpose and the motivating use case. The only gap is pagination/cursor behavior, which is minor given the schema already describes the cursor parameter.
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 100%, and the parameters (limit, cursor, employee_ids) are self-documented with defaults, bounds, and format hints. The description adds no parameter-level detail (e.g., that employee_ids expects UUIDs from receipts), so baseline 3 applies.
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?
States a specific verb and resource ('List employees') and even enumerates what counts as an employee (waiters, cashiers, staff), which is useful domain context. It does not explicitly contrast itself with the sibling get_employee, but the 'list' framing makes the bulk-vs-single distinction reasonably clear.
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?
Gives a concrete trigger: 'Use to resolve employee names from IDs found in receipts,' which tells the agent exactly when this tool is the right call. It stops short of naming the alternative (get_employee) for single-record lookups or stating when not to use it, so it is clear context without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.