Retrieves draft items generated by AI intents, covering meals, activities, lists, and more that event-only views omit. Use to review pending AI-created entries before finalizing.
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?
The description clarifies the tool's scope (general drafts vs. event-only) but does not disclose behavioral details such as pagination, ordering, or required context beyond the read-only annotation. The readOnlyHint annotation already covers side-effect safety, so the description adds moderate value.
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?
The description is a single, front-loaded sentence that states the core function and immediately clarifies its scope with a parenthetical contrast. No wasted words.
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?
While the purpose is clear, the tool has two parameters with no schema descriptions, and the description omits their semantics and doesn't cover the output format, leaving gaps an agent needs to call it correctly.
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?
Input schema has 0% description coverage, and the description does not explain what 'id' or 'frameId' mean. It only hints that items are created by an AI intent, leaving parameter meaning to inference.
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?
The description states a specific action ('List') and resource ('draft items an AI intent created'), and explicitly contrasts with the 'event-only draft list' that does not surface these items, clearly differentiating it from siblings.
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 implies when to use this tool by noting it is the 'general draft reader' covering meal sittings, activities, and list items, and that the 'event-only draft list' does not surface these. It lacks an explicit alternative name or a clear 'use when...' statement, but provides enough context for routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.