Skip to main content
Glama

solar_eclipse_series

Generates solar eclipse time-series panel images for a given date and location, or a single maximum-eclipse panel, so users can visualize the eclipse progression.

Instructions

日食の時系列パネル画像(太陽が月に欠ける過程)を返す(認証不要)。

例:「2035年9月2日の皆既日食を画像で」「東京で見える次の日食」「2019年の部分日食の進行」

Args: date: 日付(例 "2035-09-02" / "2035/09/02" / "2035年9月2日")。省略時は次の日食を検索。 place: 観測地(例 "東京","大阪","new york")。lat/lon 指定時は無視。省略時は東京。 lat: 観測地の緯度。lon と併用時は place より優先。 lon: 観測地の経度。 max_magnitude: True で最大食のみの単一パネルを返す(既定 False=時系列)。

回答時はこのリンクをそのまま提示してください(画像が描画されない環境では唯一の導線)。

Input Schema

NameRequiredDescriptionDefault
latNo
lonNo
dateNo
placeNo
max_magnitudeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed18 schema fields changedv0.41.4
    • removedInput schema / properties / date / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • removedInput schema / properties / date / default
      Removed value: -null
    • removedInput schema / properties / date / title
      Removed value: -"Date"
    • addedInput schema / properties / date / type
      Added value: +[
      +  "string",
      +  "null"
      +]
    • removedInput schema / properties / lat / anyOf
      Removed value: -[
      -  {
      -    "type": "number"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • removedInput schema / properties / lat / default
      Removed value: -null
    • removedInput schema / properties / lat / title
      Removed value: -"Lat"
    • addedInput schema / properties / lat / type
      Added value: +[
      +  "number",
      +  "null"
      +]
    • removedInput schema / properties / lon / anyOf
      Removed value: -[
      -  {
      -    "type": "number"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • removedInput schema / properties / lon / default
      Removed value: -null
    • removedInput schema / properties / lon / title
      Removed value: -"Lon"
    • addedInput schema / properties / lon / type
      Added value: +[
      +  "number",
      +  "null"
      +]
    • removedInput schema / properties / max_magnitude / title
      Removed value: -"Max Magnitude"
    • removedInput schema / properties / place / anyOf
      Removed value: -[
      -  {
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]
    • removedInput schema / properties / place / default
      Removed value: -null
    • removedInput schema / properties / place / title
      Removed value: -"Place"
    • addedInput schema / properties / place / type
      Added value: +[
      +  "string",
      +  "null"
      +]
    • removedInput schema / title
      Removed value: -"solar_eclipse_seriesArguments"
  2. Addedv0.25.2

TDQS

A4.5/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden and does well: it declares no authentication required, states the defaults (date omitted → next eclipse, place omitted → Tokyo), the precedence rule (lat/lon override place), and the output shape (time-series panel vs single max-magnitude panel). It does not mention behavior when no eclipse is visible or any rate/error conditions.

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?

Front-loaded purpose sentence, then example phrasings, then a compact Args block, then the output-handling instruction. Every line adds information the schema and annotations do not already carry.

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 covers purpose, all parameters, defaults, and how to surface the returned link to the user. The remaining gap is failure/empty-result behavior, which an agent would otherwise have to discover by calling the tool.

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 description coverage is 0%, so the description must compensate and it does fully: every one of the five parameters is explained with accepted date formats ("2035-09-02", "2035/09/02", "2035年9月2日"), place examples, lat/lon precedence over place, and the max_magnitude default of False meaning time series.

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: returns a time-series panel image of a solar eclipse (sun progressively occluded by the moon). This is distinct from siblings like moon_phase_map or sky_map_with_satellites, so an agent can pick it without opening another schema.

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?

Three concrete example queries ("total eclipse on 2035-09-02", "next eclipse visible from Tokyo", "2019 partial eclipse progression") clearly delimit the intended use context. It does not, however, route the agent away from near-neighbors such as moon_phase_map or astronomy_weather when the request is ambiguous.

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