Retrieve draft items generated by an AI intent, including meal sittings, activities, and list entries that an event-only draft list misses.
List the draft items an AI intent created (the general draft reader — meal sittings, activities, list items, etc., which the event-only draft list does not surface).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| frameId | No |
Changes observed during successful MCP inspections.
v1.0.1Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"v0.7.1Input schema / properties / id / anyOfRemoved value: -[
- {
- "type": "string"
- },
- {
- "type": "number"
- }
-]Input schema / properties / id / typeAdded value: +[
+ "string",
+ "number"
+]v0.4.6Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds genuine behavioral context by disclosing what content gets surfaced (meal sittings, activities, list items) that the event-only list omits, though it says nothing about pagination, ordering, or response size.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence that begins with the action and resource, with no filler. The nested parenthetical makes it slightly harder to parse than necessary but every clause carries meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations describing return values, so the agent gets no picture of the response shape, and the two input parameters remain unexplained. For a reader/list tool this leaves clear gaps, even though the content scope is communicated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and there are two parameters (id, frameId) that the description never mentions. With low coverage the description is expected to compensate but contributes zero meaning about what 'id' identifies or when 'frameId' is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (List) and resource (draft items created by an AI intent) and explicitly positions itself against the sibling it is not — the 'event-only draft list', i.e. skylight_list_auto_creation_drafts. The parenthetical ('meal sittings, activities, list items, etc.') clarifies the resource scope, though the phrasing is dense.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description routes the agent by contrasting this general draft reader with the event-only draft list that 'does not surface' these items, giving a clear condition for choosing this tool. It stops short of naming the sibling tool or stating explicit when-not-to-use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.