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chrischall

easytable-mcp

by chrischall

easytable_list_dates

Read-only

List bookable dates for a restaurant area and party size to see which dates are available for reservation.

Instructions

List bookable dates for a restaurant area and party size. Each entry has an ISO date and whether it is available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesRestaurant id — the `id` in a book.easytable.com/book/?id=<id> link.
langNoWidget language code (e.g. en, se, da, de, fr). Defaults to en.en
typeYesBooking area/type id from easytable_list_types.
personsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.0.0

TDQS

A3.9/5.0
Behavior4/5

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

The readOnlyHint annotation already communicates that this is a safe read operation, and the description adds useful behavioral detail by stating that each entry contains an ISO date and an availability flag. This goes beyond the annotation by describing the return shape.

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 only two sentences long, with no redundant wording. The primary action is front-loaded, and the output format is explained efficiently.

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

Completeness5/5

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

For a read-only list operation, the description is complete enough: it states the required context, output shape, and availability semantics. The schema handles the remaining parameter documentation, and no output schema means the explicit return description is 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 input schema already documents id, lang, and type, and the description loosely maps 'restaurant area' to type and 'party size' to persons. However, it does not add detail about the persons parameter's meaning or constraints beyond what the schema provides.

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 clearly states a specific action and resource: 'List bookable dates for a restaurant area and party size.' It also describes the output, which helps distinguish it from sibling tools like list_types and list_times, though it does not explicitly name those alternatives.

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 implies the tool is used when date availability is needed for a given area and party size, but it does not explicitly explain when to use this rather than easytable_list_times or other sibling tools. No exclusions or alternative routing are provided.

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