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List roles

list_roles
Read-onlyIdempotent

The workspace's roles: seats an AI assistant can take (e.g. manager, email outreach), each with how many unread messages it has. Any connected AI can act as a role.

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": "list_roles"
  }
}

Input Schema

NameRequiredDescriptionDefault
project_idNoWorkspace to work in (from list_projects). Leave out for the default one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already establish that this is a safe, idempotent, read-only operation. The description adds useful conceptual context (roles are AI seats) and discloses that each role includes an unread message count, but it does not explain ordering, whether all roles are returned, or any pagination behavior.

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 short sentences with no filler. The first sentence front-loads the resource and its key returned data; the second clarifies the role concept efficiently.

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 simple read-only list tool with annotations covering safety and a fully documented optional parameter, the description gives enough context to call it correctly. Minor omissions such as ordering or pagination are not critical for this tool shape.

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%, and the single optional project_id parameter is fully documented in the schema. The description does not add any parameter-specific meaning, such as how omitting project_id selects the default workspace, 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?

The description clearly identifies the resource (workspace roles) and explains what a role is (an AI-assistant seat such as manager or email outreach), plus that unread counts are included. It implies a list operation but does not explicitly state 'list all roles' or contrast with the sibling get_role, so it stops short of a 5.

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 the name and description—call this to see available roles and their unread counts. There is no explicit when-to-use guidance, no exclusions, and no comparison to get_role for fetching a single role.

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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