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ros2-inspector

ros2-inspector

by XuChen-AI
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_topics

Lists all ROS 2 topics and their message types to inspect active data flows and verify topic types.

Instructions

列出当前系统中的全部话题及其消息类型。

何时用：想看系统里在传什么数据、某个话题的类型是什么。 返回：topic_count 与 topics 列表（name + type 字段）。 失败时返回 error 字段。

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_topics"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It usefully states the return shape (topic_count, topics list with name and type, and an error field on failure), but omits safety profile, authentication needs, rate limits, or pagination behavior. Moderate transparency for a read-like operation.

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 short sentences, front-loaded with purpose, then usage, then return values. No redundancy, filler, or tangential detail. Every sentence earns 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?

This is a low-complexity tool with an empty input schema and no output schema. The description compensates by specifying the return shape (topic_count plus topics with name and type fields, and an error field on failure), giving the agent enough to call and interpret results.

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 the schema provides no parameter semantics to supplement. Per the rules, a zero-parameter tool earns a baseline of 4, and the description appropriately adds no unnecessary parameter detail.

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?

States a specific verb '列出' (list) and resource '全部话题' (all topics) plus message types, making the action clear. It does not explicitly differentiate from sibling get_topic_info, but the '全部' scope implies bulk listing versus single-topic detail.

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

Usage Guidelines4/5

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

Provides explicit when-to-use guidance: '想看系统里在传什么数据、某个话题的类型是什么。' This gives clear context for selection. However, it does not name alternatives (e.g., get_topic_info for one topic) or state when not to use the tool.

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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