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List users

paymo_list_users
Read-only

List users in the company (id, name, email, type, hourly rate, assigned/managed projects). Paymo: GET /api/users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOnly users of this type.
limitNoMax items to return (default 100, max 500). Paymo has no pagination; results beyond this are truncated.
whereNoExtra raw Paymo filter ANDed onto the typed ones, e.g. `billable=true` or `name like Website`. Operators: = > >= < <= != like, not like, in (a,b), not in (a,b).
activeNotrue = active users only, false = retired users only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

The readOnlyHint annotation already establishes that this is a safe read operation. The description adds some value by listing the returned fields and the underlying API endpoint, but it does not describe pagination, rate limits, authentication needs, or return formatting beyond the field names. The schema itself covers truncation behavior in the limit parameter.

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 front-loaded with the core purpose, followed by the returned fields and API endpoint. It is a single efficient sentence with no redundant or wasted language.

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 list tool with a fully documented schema and a readOnly annotation, the description is largely complete: it states purpose, returned fields, and endpoint. It could be slightly stronger by mentioning filtering options or that results are returned in a single batch, but those details are covered by the schema.

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%, so the baseline score of 3 applies. The description lists output fields (id, name, email, type, hourly rate, assigned/managed projects) rather than explaining parameter semantics, and adds no meaning beyond the fully documented schema.

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 states a specific verb and resource: 'List users in the company.' It also lists the returned fields, making the tool's output scope clear. However, it does not explicitly differentiate itself from the many sibling list_* tools, relying on the resource name alone.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives, nor any mention of when not to use it. The description does not reference the schema's filtering parameters or sibling tools that might be more appropriate for other user-related queries.

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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