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engawa

engawa

by tsuru0805
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sky_tonight

Find out what's in the sky tonight: moon phase, illumination, moonrise/set, sunset, next full/new moon, and naked-eye planets at 21:00. Computed locally, works offline.

Instructions

Tonight's sky: moon phase, illumination, moonrise/set, sunset, next full/new moon, and which naked-eye planets are up at 21:00.

Computed locally (set ENGAWA_LAT / ENGAWA_LON for your location) — the one tool here that never touches the network.

Args: date: "YYYY-MM-DD"; empty = today (local timezone)

Returns: {ok, date, moon_phase, moon_illumination, moonrise, moonset, sunset, next_full_moon, next_new_moon, planets_2100}

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": "sky_tonight"
  }
}

Input Schema

NameRequiredDescriptionDefault
dateNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral aspects: it computes locally, requires environment variables (ENGAWA_LAT/ENGAWA_LON), and never touches the network. It also specifies the return structure and date handling, offering complete transparency beyond what structured fields would provide.

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?

The description is well-structured and front-loaded with the core purpose, then concise details about computation and arguments. Every sentence adds value, and the return format is listed clearly. There is no redundancy or wasted words.

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?

Given the tool's simplicity (one optional parameter) and no output schema, the description covers all necessary context: the exact computation method, network behavior, environment prerequisites, and the full list of returned fields. It is complete for an agent to select and invoke correctly.

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?

The single parameter 'date' is fully explained: it must be in 'YYYY-MM-DD' format, and an empty string defaults to today in the local timezone. This adds substantial meaning beyond the schema, which has no description for the parameter.

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?

The description clearly defines the tool's purpose: it provides tonight's sky information including moon phase, illumination, rise/set times, sunset, next full/new moon, and visible planets. This is specific and distinct from sibling tools like apod or daily_art, which focus on other content types.

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?

The description indicates this is the only local, network-free tool, implying it should be used when offline or for sky data. It also explains the optional date parameter. However, it does not explicitly contrast with alternatives or state when not to use it, so it stops short of a perfect score.

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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