Get the current position of China's Tiangong space station. Returns live latitude, longitude, altitude, and speed computed from CelesTrak TLE data with a map link.
天宮（Tiangong）中国宇宙ステーションの現在位置を返す。
例:「天宮の現在位置」「中国宇宙ステーションは今どこ？」
CelesTrak の最新 TLE を SGP4 で伝播して現在の緯度・経度・高度・速度を計算。
認証不要。content に表示用サマリ＋Googleマップリンク、structuredContent に JSON。
Returns:
CallToolResult: 表示用サマリ + JSON。
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.25.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses the data source (latest CelesTrak TLE), the computation method (SGP4 propagation), that no authentication is required, and the output shape (display summary + Google Maps link in content, JSON in structuredContent). It omits rate limits or TLE staleness/caching behavior, which keeps it short of a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded, followed by examples and then implementation/output details, which is a sensible order. The trailing 'Returns: CallToolResult: 表示用サマリ + JSON' largely restates the earlier 'content に表示用サマリ… structuredContent に JSON', adding mild redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read tool with no output schema, the description covers trigger context, data source, auth, and output channels adequately. It stops short of enumerating the JSON fields an agent would receive, so it is complete enough but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the rubric the baseline is 4. There is nothing parameter-related for the description to compensate for.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (return current position) and resource (Tiangong Chinese space station), and the scope is unambiguous against siblings like iss_now and sat_tle. An agent can immediately tell this computes Tiangong's live position rather than returning raw TLEs or another station's data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides concrete user-phrasing examples ("Tiangong's current position", "where is the Chinese space station now?") that clearly signal when to invoke it. It stops short of naming alternatives (e.g., iss_now for the ISS, sat_tle for raw orbit data) or when-not-to-use conditions, so it is clear context without explicit routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.