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ingalgi-krishna

Dunefox Voice MCP Server

List agents (names only)

list_agents
Read-only

List workspace AI agents with ID, name, and active status to choose one for calls or announcements. Use get_agent for full prompt, voice, or script details.

Instructions

This workspace's AI agents: id, name, active. Enough to choose one for place_call or send_announcement. For an agent's full setup (prompt, voice, one-way script), use get_agent — it needs the separate "agents" scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds real behavioral context beyond the schema: it is names-only (id, name, active) and it discloses that get_agent needs an extra auth scope, which is useful for planning calls. It stops short of describing ordering or whether archived agents are included.

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?

Three tight sentences, front-loaded with what the tool returns before the alternative. Every clause earns its place: what you get, why it's enough, and where to go for more.

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?

For a no-parameter, read-only list tool with no output schema, the description covers the return fields, the purpose, and the sibling alternative including a scope caveat. Nothing an agent needs to call it correctly is missing.

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?

There are zero parameters, so the baseline is 4. The description correctly adds no parameter guidance because none is needed, and instead spends its words on return shape and sibling routing.

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 concrete verb+resource (list this workspace's AI agents) and immediately specifies the returned fields (id, name, active). It also explicitly distinguishes itself from get_agent, so an agent can tell the two apart without opening either 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?

Gives a positive use case (enough to choose an agent for place_call or send_announcement) and an explicit alternative with its condition (full setup via get_agent, which requires the separate "agents" scope). When-to-use and when-to-use-something-else are both covered.

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