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space-finder-mcp

by loosephoto
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Python
Local

constellation_now

Compute altitudes, azimuths, and constellations of the Sun, Moon, and planets for a given location and time using NASA JPL ephemeris data locally.

Instructions

指定した観測地・日時で太陽・月・惑星の位置（高度・方位角・星座）を返す。

「今夜東京で見える惑星は?」など。NASA JPL 天体暦 + Skyfield でローカル計算（認証不要）。

Args:
    latitude: 観測地の緯度（例 東京 35.68）。place 指定時は省略可。
    longitude: 観測地の経度（例 東京 139.69）。
    place: 観測地名（既知テーブル）。緯度経度より優先。
    time_utc: 観測時刻 "YYYY-MM-DD HH:MM"（UTC）。省略で現在。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
placeNo
latitudeNo
time_utcNo
longitudeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.25.2

TDQS

A4/5.0
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 a decent job: it discloses local computation via NASA JPL ephemeris + Skyfield, that no authentication is needed, and that omitting time_utc defaults to 'now'. It does not discuss response format or numeric precision/frame, but the key operational traits 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 summary, then a concrete query example, then an Args block — well organized with no filler. The example sentence and the ephemeris note each earn their place.

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?

For a 4-parameter read/compute tool with no output schema, the description names the returned quantities (altitude, azimuth, constellation) and the input semantics fully. It could say slightly more about the return structure, but nothing required 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.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, yet the description documents all four parameters — latitude/longitude with a Tokyo example, place as a known-name lookup, and time_utc with its format and default. It even states the precedence rule that place overrides latitude/longitude, adding meaning absent from the schema.

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 (返す) and precise resource — altitude, azimuth, and constellation of Sun/Moon/planets for a given site and time. It is distinguishable from most siblings, though it does not explicitly contrast itself with the nearby solar_system_now tool.

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

Usage Guidelines3/5

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

The '「今夜東京で見える惑星は?」' example gives a concrete use case, which implies when to reach for it. However, there is no explicit when-not guidance and no routing to alternatives such as solar_system_now, leaving comparison to inference.

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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