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chrischall

skylight-mcp

by chrischall
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

skylight_generate_meal_plan

Generate AI-based meal plans for selected dates, producing draft meal sittings that you can review and approve after they are ready.

Instructions

Generate an AI meal plan for the given dates (creates draft meal sittings — async; poll with skylight_get_auto_creation_intent, then approve).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datesYesYYYY-MM-DD dates to generate meals for.
frameIdNo
recipe_sourceNoDefaults to 'generate' (AI-generated).
mouths_to_feedNoHow many people to feed.
meal_category_idYesMeal category id (from skylight_list_meal_categories).
add_to_grocery_listNo

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. Changed2 schema fields changedv0.7.1
    • removedInput schema / properties / meal_category_id / anyOf
      Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "number"
-  }
-]
    • addedInput schema / properties / meal_category_id / type
      Added value: +[
+  "string",
+  "number"
+]
  3. First observedv0.4.6

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only state readOnlyHint=false and destructiveHint=false, which tells the agent this is a mutation but not what kind. The description usefully discloses that the tool is asynchronous, creates drafts rather than final meals, and requires a follow-up poll and approval step. This adds meaningful behavioral context beyond the annotations.

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 one tight sentence that front-loads the core purpose and then packs the essential async workflow into a parenthetical. Every phrase earns its place, and the sibling tool names for polling are included.

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 an async mutation tool with no output schema, the description covers the critical workflow: creating drafts, polling with skylight_get_auto_creation_intent, and approving. It is slightly incomplete because it does not name the 'approve' tool explicitly and leaves some parameter semantics unresolved, but overall it gives an agent enough context to proceed.

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

Parameters2/5

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

The description adds no parameter-level meaning beyond what is already in the input schema; it only references 'the given dates.' Schema coverage is 67%, leaving frameId and add_to_grocery_list completely undocumented in both schema and description, and the description does not compensate for this gap.

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 ('Generate an AI meal plan') and the resource ('for the given dates'), and it adds the important nuance that the result is draft meal sittings. However, it does not explicitly distinguish itself from the similarly named sibling tool skylight_plan_meal, so an agent may need to inspect both tools to choose correctly.

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 clear usage context: use this to generate an AI meal plan for specific dates, and then explains the async workflow ('poll with skylight_get_auto_creation_intent, then approve'). It does not explicitly mention exclusions or alternative tools, so it stops short of full routing guidance.

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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