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hr-assist

hr-assist

by Jayeshm93
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_employee_details

Retrieve an employee's ID and manager ID by name to assist with HR onboarding workflows.

Instructions

Get employee details by name. :param name: Name of the employee :return: Employee ID and manager ID

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "get_employee_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. It clearly indicates a read-only 'Get' operation and exposes the return fields. However, it lacks details on matching behavior (e.g., exact vs. partial name, case sensitivity) and error handling when an employee is not found, leaving important gaps.

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 concise and front-loads the main purpose. The param and return lines are clearly separated and add useful information without redundancy. It is slightly less polished than a purely declarative sentence but remains well-structured and free of filler.

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?

The tool is a simple lookup with one parameter and an output schema exists, so the description covers the essential request and response shape. However, it lacks usage guidance relative to sibling tools and does not address ambiguity or failure cases. Overall, it is minimally complete but has noticeable gaps.

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?

The schema has no description for the 'name' parameter (0% coverage), so the description's ':param name: Name of the employee' adds minimal meaning beyond the parameter name itself. It does not specify format, case sensitivity, or matching semantics, so it fails to compensate for the schema's lack of detail.

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

Purpose5/5

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

The description clearly states a specific verb and resource: 'Get employee details by name.' It also specifies the return values (Employee ID and manager ID), making the purpose unambiguous. This distinguishes it from the sibling tool get_employee_leave_balance, which focuses on leave data.

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?

The description provides no guidance on when to use this tool versus alternatives such as get_employee_leave_balance or list_tickets. It does not mention exclusions, prerequisites, or preferred use cases. The only implied usage is from the verb 'Get,' which is not sufficient.

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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