FogBugz

List People

list_people

Read-only

Retrieve all FogBugz users with their IDs, names, and email addresses to identify correct assignees before creating or updating cases.

Instructions

Lists all people (users) in FogBugz with their IDs, names, and email addresses. Useful for finding the correct assignee name or ID before creating or updating a case.

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_people"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.9.8Apr 19, 2026

TDQS

A4.7/5.0

Behavior4/5

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

Annotations declare readOnlyHint=true, which the description aligns with by implying a safe read operation ('Lists'). The description adds value by specifying the returned fields (IDs, names, emails) and the tool's utility for assignee lookup, which annotations don't cover. No contradictions exist, and it provides useful behavioral context beyond annotations.

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 first states what the tool does and what it returns, the second explains when to use it. It's front-loaded with core functionality and efficiently structured, making every sentence earn its place.

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?

Given the tool's low complexity (0 parameters, read-only), annotations cover safety, and the description clearly explains purpose, usage, and output fields. No output schema exists, but the description specifies returned data (IDs, names, emails), making it complete for this context without over-explaining.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate. A baseline of 4 is applied for zero parameters, as it avoids unnecessary details and focuses on the tool's purpose.

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 clearly states the verb ('Lists') and resource ('all people (users) in FogBugz'), specifies the returned fields ('IDs, names, and email addresses'), and distinguishes from siblings by focusing on user data rather than cases, projects, or other entities. This is specific and unambiguous.

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

Usage Guidelines5/5

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

It explicitly states when to use this tool: 'Useful for finding the correct assignee name or ID before creating or updating a case.' This provides clear context and ties usage to sibling tools like create_case or update_case, offering practical guidance without being misleading.

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