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AniketDonode

Leave Manager

by AniketDonode

submit_leave_request

Submit a new employee leave request by providing employee ID, dates, leave type, reason, and days requested, so leave can be reviewed and approved.

Instructions

Submit a new leave request

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonYes
end_dateYes
leave_typeYes
start_dateYes
employee_idYes
days_requestedYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, but it only implies a mutation ('Submit') without stating permissions required, validation rules, whether approval is triggered, or what happens to existing data. It reveals that a write occurs but nothing about side effects or constraints.

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

Conciseness3/5

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

The single sentence is front-loaded and free of filler, but it is under-specified relative to the tool's complexity. Brevity here functions as omission rather than efficiency, since the sentence adds almost nothing beyond the tool name.

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

Completeness2/5

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

An output schema exists, so return values need not be described, but the input side is severely under-documented: six required parameters with no schema descriptions and no annotation coverage. For a mutation tool that likely interacts with leave balances and approval workflows, the description should convey more context to prevent malformed calls.

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

Parameters1/5

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

Schema description coverage is 0% and there are six required parameters, yet the description adds no meaning for any of them. It does not explain formats for dates, allowable values for leave_type, the relationship between start_date/end_date and days_requested, or the employee_id semantics.

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 states a specific verb ('Submit') and resource ('a new leave request'), making the tool's core action immediately clear. It does not explicitly differentiate itself from siblings like approve_leave_request or check_leave_balance, so an agent must rely on tool names to disambiguate.

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 offers no when-to-use guidance, no prerequisites, and no mention of alternatives such as checking leave balance first. It simply restates the action, leaving the agent to infer the appropriate context without help.

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