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shrey715

Mess MCP Server

cancel_meal

Cancel a previously registered meal for a chosen date and meal type. Check your monthly cancellation count first to confirm the cancellation is allowed.

Instructions

Cancel a meal registration.

Monthly cancellation limits may apply. Check get_cancellation_count first.

Args: meal_date: Target date (YYYY-MM-DD). meal_type: One of 'breakfast', 'lunch', 'snacks', 'dinner'. api_key: API key. Falls back to MESS_API_KEY environment variable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
meal_dateYes
meal_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It clearly implies a mutating action and adds useful constraints (monthly limits, API key fallback), but it does not explain whether the cancellation is reversible, what side effects occur, or how failures are signaled. It is adequate but not deeply transparent.

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 short, front-loaded with the action, and scannable with a clear Args block. Every sentence adds useful information, and there is no filler or repetition of schema details.

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?

For a simple three-parameter cancellation tool, the description covers the operation, the limit-related prerequisite, authentication, and all parameter semantics; an output schema also exists. It is slightly incomplete in not addressing reversibility or when a cancellation cannot be made, but overall an agent has enough to invoke it correctly.

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?

The input schema provides no descriptions or enums, but the description fully compensates: it gives the exact date format, lists the allowed meal_type values, and explains the api_key fallback behavior. This is strong parameter-level guidance beyond the structured 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?

The description uses a specific verb ('Cancel') and a precise resource ('a meal registration'), making the operation unmistakable. It is clearly distinct from siblings like uncancel_meal and register_meal, and the action is obvious without needing to open the schema.

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

Usage Guidelines4/5

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

The description gives explicit context: monthly cancellation limits may apply and the agent should check get_cancellation_count first. It does not explicitly state when not to use the tool or point to alternatives like uncancel_meal for undoing a cancellation, but the prerequisite guidance is clear and actionable.

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