AEO Copilot MCP Server

add_prompts

Bulk-add prompt strings to a brand under a selected topic. Helps build prompt collections while enforcing your plan's monthly prompt limit.

Instructions

Bulk-add prompts to a brand under a specific topic. Subject to your plan's monthly prompt limit — the API will return an error if you've reached it.

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": {
      "brandId": "<brandId>",
      "topicId": "<topicId>",
      "prompts": "<prompts>"
    },
    "name": "add_prompts"
  }
}

Input Schema

Name	Required	Description
`brandId`	Yes	The brand UUID from list_brands
`prompts`	Yes	Array of prompt strings to add
`topicId`	Yes	The topic UUID from list_topics — prompts are grouped under a topic

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Aug 30, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden, and it delivers a meaningful disclosure: the operation is subject to a monthly prompt limit and will return an error when exhausted. This is exactly the kind of rate-limit context the rubric credits. It stops short of revealing partial-failure or deduplication semantics for the bulk write, but the disclosed error condition is substantive.

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?

Two sentences with zero waste. The verb and resource are front-loaded in the first sentence, and the second sentence adds a single high-value constraint. Every word earns its place.

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 a low-complexity bulk-add tool with three fully documented parameters, the description covers purpose, scope, and the primary failure condition. No output schema exists, so the return value is never described, and partial-failure behavior is unaddressed — but the open questions are minor given how simple the call is.

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 100% — all three parameters (brandId, topicId, prompts) are already documented with source hints ('from list_brands', 'from list_topics') and types. The description's 'under a specific topic' phrase merely restates the schema's topicId semantics rather than adding new parameter meaning, so baseline 3 applies.

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 ('Bulk-add'), resource ('prompts'), and scope ('to a brand under a specific topic'), which clearly distinguishes this from index-scoped siblings like add_index_prompts. However, it doesn't explicitly name alternatives, so differentiation is implied rather than stated.

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 context is implied by the action itself — adding prompts to a brand under a topic — and the plan-limit warning functions as a constraint on when to call it. But there is no explicit guidance about when to prefer this over update_prompts, add_index_prompts, or run_brand_prompts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.