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skylight_list_meals

Read-only

Retrieve planned meals across a date range to see each day's meal plan, meal slots, linked recipes, and assigned family members.

Instructions

List planned meals (meal sittings) in a date range — what is on the meal plan for each day. Each sitting carries the dates it falls on in its instances array, its meal slot in meal_category (breakfast/lunch/dinner), its linked recipe in meal_recipe, and the family members it is assigned to in profiles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frameIdNo
date_maxYesYYYY-MM-DD inclusive upper bound (required by the API).
date_minYesYYYY-MM-DD inclusive lower bound (required by the API).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv0.7.1

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuine context beyond that by enumerating what each sitting carries (instances, meal_category, meal_recipe, profiles), which is meaningful given there is no output schema. It stops short of pagination or scope limits.

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?

Front-loaded with the operation and scope, then a single sentence enumerating returned fields. Every clause earns its place given the absence of an output schema, though the second sentence is dense with backtick-quoted field names.

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 read-only list tool with no output schema, the description supplies the return shape and the date-range contract, which is what an agent most needs. Missing pieces are minor: an explanation of frameId and any result-size or pagination behavior.

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?

Two of three params (date_min, date_max) are already documented in the schema with format and inclusivity notes, and the description adds only the broad 'date range' concept. The third parameter, frameId, is undocumented in both schema and description, leaving a real gap that the 67% coverage baseline reflects.

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?

Specific verb+resource ('List planned meals (meal sittings) in a date range') with a clarifying gloss ('what is on the meal plan for each day'). An agent can distinguish it from mutating siblings like skylight_plan_meal or skylight_update_meal, but the description never explicitly names those alternatives the way a tier-5 definition would.

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?

Usage is only implied by the required date range; there is no explicit when-to-use or when-not, and no routing to siblings such as skylight_generate_meal_plan or skylight_list_meal_categories. The definition assumes the agent already knows it wants a meal-plan read.

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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