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ncreighton

astro-cosmic-weather-mcp

by ncreighton

moon_phases

Retrieve moon phase events (new moon, first quarter, full moon, last quarter) within a specified date range, defaulting to the next 90 days. Answers questions like 'When is the next full moon?'

Instructions

List New Moon / First Quarter / Full Moon / Last Quarter events within a date range. Use this when the user asks "when is the next full moon?", "list the moon phases this month", or "when was the last new moon?". If no range is given, the API defaults to now through +90 days.

Args: from_date: Start of the range, ISO 8601 (e.g. "2026-08-01"). Omit for "starting now". to_date: End of the range, ISO 8601 (e.g. "2026-11-01"). Omit for "90 days from the start". tz: IANA timezone name for the returned event timestamps and any local-time labeling. Defaults to "UTC".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tzNoUTC
to_dateNo
from_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the default date range (now through +90 days) and clarifies timezone handling (IANA timezone for returned timestamps and local-time labeling). This is meaningful behavioral context, though it does not mention auth/rate limits or sorting behavior.

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 tightly structured: purpose statement, usage examples, default behavior, then parameter breakdown. Every sentence adds value, with no fluff or repetition. Front-loaded with the core function.

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 presence of an output schema (which handles return field details), the description sufficiently covers the main behavioral aspects: what is returned (four phase types), date range semantics, default behavior, and timezone handling. The examples ensure the agent can select this tool appropriately among numerous siblings.

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 schema has 0% description coverage, but the description fully compensates. Each parameter (from_date, to_date, tz) is explained with ISO 8601 examples, defaults, and semantic meaning (e.g., 'Omit for starting now'). This exceeds the baseline and leaves no ambiguity.

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 opens with a specific verb 'List' and explicitly names the four moon phase events (New Moon / First Quarter / Full Moon / Last Quarter) within a date range. This clearly distinguishes from siblings like moon_current (which returns the current phase) and moon_void_of_course.

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?

Provides explicit when-to-use guidance with concrete example queries ('when is the next full moon?', 'list the moon phases this month'). Does not explicitly state when not to use or name alternative sibling tools, but the examples effectively communicate the intended use case.

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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