AEO Copilot MCP Server

list_topics

Retrieve all topics configured for a brand, showing how related prompts are grouped into categories such as Product Comparisons and Feature Questions. Provide a brand ID to get the list.

Instructions

List all topics configured for a brand. Topics group related prompts together (e.g. 'Product Comparisons', 'Feature Questions').

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>"
    },
    "name": "list_topics"
  }
}

Input Schema

Name	Required	Description	Default
`brandId`	Yes	The brand UUID from list_brands

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Aug 30, 2026

TDQS

A4.3/5.0

Behavior4/5

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

There are no annotations, so the description carries the transparency burden; it clearly indicates a read-only listing behavior ('List all topics') and notes that topics organize prompts. It does not discuss empty results or pagination, but for a simple read tool the core behavior is adequately disclosed.

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?

The description is two sentences with the main operation front-loaded and examples to clarify what a topic is. There is no redundant or filler text.

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 one-parameter read tool with fully described parameters, the description supplies enough context: what the tool returns, how topics relate to prompts, and the brand scope. No output schema is present, but the expected output is self-evident from 'List all topics'.

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% because brandId is already described as 'The brand UUID from list_brands'. The tool description restates the brand scope but does not add new parameter guidance beyond the schema.

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?

The description uses a specific verb ('List'), identifies the resource ('topics'), and scopes it to a brand. It also defines topics as groupings of related prompts, which separates this tool from sibling tools like list_prompts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The statement is clear that this tool is for retrieving all topics configured for a given brand, and the topic-grouping context implies 'use this when you need topic structure rather than raw prompts.' It does not explicitly name alternatives or when-not-to-use conditions, so it falls just short of a 5.

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