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XuChen-AI

ros2-inspector

by XuChen-AI

system_overview

Fetch a one-page snapshot of ROS2 system state, including nodes, topics, connections, and counts. First step for status questions; drill down with detailed tools.

Instructions

获取当前 ROS2 系统的一页式快照:节点、话题、连接关系与数量统计。

何时用:回答"系统现在什么状态"类问题的第一入口——先看总览, 发现异常节点/话题后再用 get_node_info / get_topic_info / sample_topic 下钻。 返回:node_count / topic_count 统计、nodes 列表、topics 列表(含类型)、 connections(每个节点的发布/订阅概况)。节点数超过 12 个时只展开前 12 个 (notes 字段会注明)。失败时返回 error 或 notes 说明原因,不会中断会话。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full behavioral burden, and it does disclose meaningful traits: the 12-node expansion cap with a notes field caveat, and failure semantics (returns error/notes without interrupting the session). It stops short of describing read-only guarantees or performance/cost characteristics, but the operational behaviors that matter for invocation are covered.

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?

Front-loaded with the purpose, then clearly sectioned into usage and returns, with no filler. The return section enumerates several field names, which is slightly verbose, but each line earns its place by clarifying scope or output shape.

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?

With no output schema and no annotations, the description supplies exactly what is missing: the return payload structure (node_count/topic_count, nodes, topics with types, connections), the truncation rule, and failure handling. An agent has everything needed to call it and interpret the result.

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 and schema coverage is complete, so there is nothing for the description to document. Baseline 4 applies; the description correctly adds no parameter noise.

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: a one-page snapshot of the current ROS2 system covering nodes, topics, connections and counts. It also implicitly scopes itself against the drill-down siblings, so an agent can distinguish it from list_nodes/get_node_info 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 designates itself as the first entry point for "what is the system state now" questions, and names the follow-up alternatives (get_node_info / get_topic_info / sample_topic) with the condition that triggers them (an anomalous node/topic is found). When-to-use and when-to-escalate are both stated.

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