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Sushmitha26

Employee Leave Management MCP Server

by Sushmitha26

cancel_leave

Cancel a leave request by providing its request ID. If the leave was already approved, the canceled days are automatically credited back to the employee's balance.

Instructions

Cancel a leave request. If it was already approved, the days are credited back to the employee's balance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the side-effect of credit-back for approved requests, which is useful. However, it does not mention the reverse direction, prerequisites (e.g., can all requests be canceled?), or what happens to pending vs rejected requests besides approved ones.

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?

Two concise sentences with no filler. The core purpose and a key behavioral nuance (credit-back) are communicated efficiently. Slightly more detail on edge cases could have been added without hurting length.

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 simple single-parameter cancellation tool with no output schema, the description is reasonably complete. It covers the main action and the most consequential side-effect (balance credit-back for approved requests). Missing: what happens to already-rejected requests, whether cancellations require permissions, and any constraints on when cancellation is allowed.

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

Parameters3/5

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

Only one parameter exists (request_id), which is self-explanatory as an integer identifier given the tool name. Schema coverage is 0%, but with a single obvious parameter, the schema plus name largely convey meaning. The description adds no additional param detail, but very little is genuinely needed here.

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?

Clear verb+resource: 'Cancel a leave request.' The description explicitly distinguishes the operation and adds behavioral context (credit-back on approved requests). It differentiates from siblings by targeting a specific request state (approved vs pending) effect.

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 what happens when canceling an approved request (days credited back), giving implied context on when this is appropriate. However, it does not explicitly say when to use this vs reject_leave or other alternatives, nor provide exclusions.

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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