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IIITH Mess MCP

IIITH Mess MCP

by Kallind
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

mess_cancel_registration

DestructiveIdempotent

Cancel a booked meal registration to avoid charges by specifying the meal date and type. Use before the cancellation deadline to prevent billing.

Instructions

Cancel a meal registration so the user is not charged for it.

Use when the user wants to cancel/drop a booked meal. Returns 403 if the cancellation window is closed, 424 if no registration exists.

Args: params: auth_key/session, meal_date, meal_type

Returns: JSON status 204 on success

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": {
      "params": "<params>"
    },
    "name": "mess_cancel_registration"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.4/5.0
Behavior4/5

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

The description adds valuable behavioral context beyond annotations: it specifies error conditions (403 if cancellation window is closed, 424 if no registration exists) and the success response (JSON status 204). Annotations already indicate destructive (true), idempotent (true), and openWorld (true), but the description provides concrete failure modes and success semantics, enhancing transparency without contradiction.

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 front-loaded with the purpose, followed by usage guidelines, error conditions, and parameter/return details in a structured format. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 the tool's complexity (destructive operation with error conditions), the description is mostly complete: it covers purpose, usage, errors, parameters, and returns. Annotations provide safety hints, and there is an output schema (implied by 'Returns'), so the description doesn't need to detail return values. It could improve by explaining idempotency or openWorld implications, but it's largely sufficient.

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?

The description lists parameters (auth_key/session, meal_date, meal_type) but does not add meaning beyond the input schema, which has 0% description coverage. Since schema coverage is low, the description partially compensates by naming parameters, but lacks details on formats or constraints. With 0% coverage, baseline is lower, but the description provides some param info, warranting a score of 3.

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 the tool's purpose with a specific verb ('cancel') and resource ('meal registration'), and distinguishes it from siblings by focusing on cancellation rather than creation, deletion of other resources, or other operations. It directly explains what the tool does: 'Cancel a meal registration so the user is not charged for it.'

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool: 'Use when the user wants to cancel/drop a booked meal.' It distinguishes from alternatives by implying this is for cancellations, unlike sibling tools like mess_create_registration or mess_skip_meal, and mentions specific error conditions (403, 424) that help determine appropriateness.

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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