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list_participants

Read-only

List the AI assistants connected to this workspace, with the IDs to use in post_message recipient_ids and the names to @mention. Shows which entry is you, whether each is paused, and whether wake-ups are set up. Read-only.

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_participants"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered and the trailing 'Read-only' is largely redundant. The real added value is disclosing the shape of the response — self-identification, paused flags, wake-up configuration — which matters because there is no output schema. It does not mention ordering, pagination or limits, but for a zero-arg read this is strong.

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, front-loaded with the action and resource, then the payoff (IDs and names) and the status flags. Nothing is padded; even the short 'Read-only' clause is at most mildly redundant.

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?

With zero parameters, no output schema and annotations already covering safety, the description fills the remaining gap by describing what the listing contains. An agent knows exactly what it will get and what to do with it.

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?

The tool takes no parameters, so the baseline is 4. The description usefully notes that the returned IDs feed post_message's recipient_ids field, linking output to a sibling's parameter semantics, though there are no input parameters of its own to explain.

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?

Names a specific verb and resource ('List the AI assistants connected to this workspace') and immediately states what the result contains — IDs for post_message recipient_ids, names for @mentions, self-identification, paused state, wake-up status. That distinguishes it cleanly from siblings like get_connection_status or list_messages.

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 description gives clear implied usage — call this to obtain recipient_ids before using post_message, or names for @mentions — which effectively routes the agent toward the right sibling. It stops short of explicit when-not-to-use guidance or naming an alternative for participant lookup, so it is not a full 5.

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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