Engagemii AI Visibility Data

List data orders and download links

data_orders

Read-onlyIdempotent

List the data orders on the account behind an Engagemii data API key: order number, records, date, status (preparing, ready or pending), the refresh of scores older than 30 days (state, how many rows were stale, how many are rescored so far, when the refreshed file was ready), and a download link for each ready file. The same as GET https://api.engagemii.com/api/v1/data/orders. Requires an Engagemii data API key.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "data_orders"
  }
}

Input Schema

Name	Required	Description	Default
`api_key`	No	Your Engagemii data API key (edk_...). Only needed when the key is not already sent as a request header.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 22, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, so the description doesn't need to re-establish safety. It does add real value by disclosing the status enum (preparing, ready, pending), the 30-day staleness refresh semantics, and that an Engagemii data API key is required — context not present in 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and return fields, then auth and endpoint mapping. It is one dense run-on sentence with a long parenthetical about refresh state, which is slightly heavy but every clause carries information.

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?

With no output schema, the description carries the burden of explaining return values and does so field by field, including download links for ready files. An agent has enough to call it and interpret the response; only pagination/rate-limit behavior is unaddressed.

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

Parameters4/5

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

Only one parameter and its schema coverage is 100%, so the schema already explains the edk_ prefix and header fallback. The description reinforces the auth requirement and account scoping ('account behind an Engagemii data API key'), which adds slight context beyond the field text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (list data orders) and enumerates the returned fields — order number, records, date, status values, refresh details, download links. This distinguishes it from sibling read tools like data_records or data_signup without needing their schemas.

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 implied by describing what the tool returns and that it mirrors GET /api/v1/data/orders, but it never says when to pick this over data_records, data_signup, or dataset_sample. No exclusions or alternative-routing guidance is offered.

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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