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get_employee_details

Find an employee's HR details using only their name. Fetch work-related information such as job title, department, and contact details to support HR tasks and decision-making.

Instructions

Get the details of an employee by name.
Args:
    name: str
Returns:
    Dict[str, Any]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits itself. It implies a read-only lookup and indicates a Dict return, but it does not state what happens if the employee is not found, if multiple employees share the same name, or whether lookup is case-sensitive/exact-match.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core sentence. The Args/Returns lines are somewhat redundant with the input schema and output schema, but they do not add meaningful bloat. Overall it is efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter lookup tool with an output schema, the description is minimally viable: it states the action and parameter. However, it leaves important gaps around duplicate or missing employee names and does not position the tool against sibling employee-related tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needs to compensate for parameter meaning. It only restates that 'name' is a string and that lookup is by name, which duplicates the schema. It adds no details about name format, required specificity, or matching behavior.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Get the details of an employee by name.' This is specific and identifies both the resource (employee details) and lookup method. It does not explicitly differentiate from sibling read tools like get_leave_balance or get_leave_history, but the tool name and description are unambiguous enough.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives. It does not mention that leave-related information should go through get_leave_balance or get_leave_history, nor does it provide any context for when get_employee_details is the right choice.

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

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