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adityapatel143

Employee Leave Management MCP Server

get_leave_history

Retrieve all leave requests for an employee. Filter by year or status to review specific periods or outcomes.

Instructions

Retrieve all leave requests for an employee, optionally filtered by year or status.

Args: identifier: Employee code or email. year: Filter by calendar year. 0 = all years. status: Filter by status: "pending", "approved", "rejected", "cancelled". Leave empty to return all statuses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
statusNo
identifierYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses read-only behavior (retrieve) and optional filters, but does not mention what happens if identifier is invalid, rate limits, or data freshness. It is adequate but could provide more detail.

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

Conciseness5/5

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

The description is concise with a clear purpose sentence followed by a bullet list of parameters. No redundant information; every sentence adds value. Front-loaded with the main purpose.

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

Completeness4/5

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

Given an output schema exists (external), the description does not need to detail return values. It covers input parameters well. Could mention ordering or default time range, but overall sufficient for a simple retrieval tool.

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

Parameters5/5

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

Input schema has 0% description coverage, but the description's Args section explicitly explains each parameter: identifier as employee code or email, year as calendar year with 0 meaning all, and status with enumerated filter values. This adds essential meaning beyond the schema.

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?

Description clearly states the tool retrieves all leave requests for an employee, with optional year and status filters. The verb 'retrieve' and resource 'leave requests' are specific, and it differentiates from sibling tools that handle apply, approve, cancel, etc.

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

Usage Guidelines3/5

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

The description states when to use (to get leave history) but does not explicitly mention when not to use or compare to alternatives like get_leave_request for a single request. Usage context is implied by naming but not elaborated.

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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