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list_agents

Discover local Antigravity, Codex, Claude Code, OpenCode and configured ACP agents for delegation, research, code review, implementation and second opinions.

Instructions

Discover local Antigravity, Codex, Claude Code, OpenCode and configured ACP agents for delegation, research, code review, implementation and second opinions. Lists agent_id, command availability and configuration errors without starting agent processes, contacting models or verifying authentication. Use get_agent_info for live readiness, models and tool policies. Поиск агентов для делегирования задач. Use when asked to discover actual available local agents or while preparing authorized delegation. General explanations and advice about agents or second opinions do not require an inventory of the user's installed agents.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.8.2

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it discloses that no agent processes are started, no models are contacted, and authentication is not verified — i.e., a cheap, side-effect-free read. It does not mention latency or whether results are cached, which is the only remaining behavioral gap.

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 key capability and the negative-scope clause are front-loaded, and the routing hint to get_agent_info sits right where it is needed. The stray Russian sentence ("Поиск агентов для делегирования задач.") duplicates the first line without adding meaning, and the when-not sentence is slightly verbose, but overall it is tight.

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?

With no output schema and no annotations, the description does the work by naming the returned fields and the explicit non-effects of the call. It stops short of describing the output shape (how errors or availability are represented), which would fully close the gap given the absent output schema.

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 zero parameters, so there is nothing for the description to disambiguate; baseline for a parameterless tool is 4. The description correctly conveys that no filters exist by framing the result as the full local inventory.

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 ("Discover local Antigravity, Codex, Claude Code, OpenCode and configured ACP agents") and names exactly what the listing contains (agent_id, command availability, configuration errors). It explicitly contrasts itself with the sibling get_agent_info, so an agent can distinguish the two 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 explicit when-to-use ("when asked to discover actual available local agents or while preparing authorized delegation"), an explicit alternative ("Use get_agent_info for live readiness, models and tool policies"), and an explicit when-not ("General explanations and advice ... do not require an inventory of the user's installed agents"). Nothing is left to inference.

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