Mapples

Get API data states

get_api_data_states

Read-only

Read the saved data states of a project's API requests, by project UUID: the mock data the canvas previews each request with. success is the response body, error is {status, body} and loading is what api..data holds while loading; each is null when not set. Requires project:view (or the project's API key).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_uuid": "<project_uuid>"
    },
    "name": "get_api_data_states"
  }
}

Input Schema

Name	Required	Description	Default
`project_uuid`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 5, 2026

TDQS

A4/5.0

Behavior5/5

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

Annotations only carry readOnlyHint=true; the description adds the authentication requirement ('Requires project:view (or the project's API key)') and explains the semantics of each returned field, including that values are null when unset. It tells the agent both how to access it and how to interpret results, which goes well beyond the annotation.

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?

Two tight sentences, front-loaded with the operation and scope, followed by the field semantics and permission note. The success/error/loading explanation is dense but each clause says something distinct; no filler.

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 single-parameter read with an output schema provided, the description covers everything an agent needs: what is returned, how each state value is shaped, null behavior, and the auth prerequisite. Return-format detail beyond that is already in the output schema.

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?

Schema description coverage is 0%, so the description must carry the load; it clarifies that the UUID identifies the project being read ('by project UUID') and that states are keyed per request name via api.<name>.data. It does not describe UUID format or error behavior for unknown projects, so it partially compensates rather than fully.

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?

States a specific verb and resource: 'Read the saved data states of a project's API requests', scoped by project UUID, with the concrete gloss 'the mock data the canvas previews each request with'. That clearly separates it from get_project, get_project_style and get_selection, though no sibling is named explicitly.

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 scope ('a project's API requests') implies when to reach for it, and the permission requirement is stated, but there is no explicit when-to-use/when-not guidance or pointer to alternatives for getting project data. Usage is inferable rather than spelled out.

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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