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List Agents

list_agents
Read-only

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
on_behalf_ofNoAn agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account.
include_completedNoSet to True to include completed agents.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / on_behalf_of
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "An agency client's email, from list_agency_clients, to run this call in that client's account: their agents, settings, connected accounts, and credits. Omit it to act on your own account."
      +}
  2. Changed1 schema field changed
    • changedInput schema / properties / include_completed / description
      Previous value: -"Set to True to include completed tasks."New value: +"Set to True to include completed agents."
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true, but the description adds substantial operational detail beyond that: completed agents are excluded by default, trigger_count only counts triggers that can still fire (one-time fired triggers excluded), and the return value is a dict with an 'agents' key that is not directly iterable. This is exactly the kind of context annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The summary is front-loaded and the XML-tagged returns block is justified because there is no output schema. It is slightly redundant, repeating the get_agent_details pointer in both the summary and returns section, but overall it is well organized and each part serves a purpose.

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 a simple read-only list tool with no output schema, the description fully compensates by documenting the return structure, key access pattern, per-field contents, and omitted fields. With annotations covering safety and the schema covering inputs, nothing an agent needs to call this correctly is missing.

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 both parameters (on_behalf_of, include_completed) are already fully documented in the schema. The description only restates the default-excludes-completed behavior, adding no syntax, format, or constraint detail beyond what the schema provides; a baseline 3 is appropriate.

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?

States a specific verb and resource ('List the user's agents') and enumerates what each summary contains: status, run counts, trigger count. It also names and differentiates the sibling tool get_agent_details(agent_id) for goal, workspace, and full trigger bodies, so an agent can tell the two apart without opening a schema.

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?

Explicitly provides the alternative route: use this tool for one-line summaries, and drill into a single agent with get_agent_details(agent_id) when goal, workspace, or full trigger bodies are needed. That effectively communicates both when to use this and when to switch tools, with no inference required.

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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