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get_nightly_forecast

Retrieve a curated list of the best celestial objects to observe tonight, including moon phase, visible planets, and deep-sky objects based on your location and time.

Instructions

Get a curated list of best objects to view for the night.

Args: lon: Observer longitude in degrees lat: Observer latitude in degrees time: Date string "YYYY-MM-DD HH:MM:SS" (Time of observation, or just date) time_zone: IANA timezone string limit: Max number of deep-sky objects to return (default 20)

Returns: Dict with keys: - moon_phase: Moon details - planets: List of visible planets - deep_sky: Sorted list of deep sky objects (Messier/NGC)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lonYes
latYes
timeYes
time_zoneYes
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a dict with moon_phase, planets, and deep_sky, and that deep_sky is sorted. However, it doesn't mention data freshness or any constraints beyond parameters.

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 concise and well-structured: a one-line purpose, bullet points for parameters, and clear return format. Every sentence adds value without redundancy.

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 output schema exists and the description explains the return keys, the tool is completely specified. It covers the necessary context for an agent to decide 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 description adds detailed meaning for all 5 parameters, including latitude/longitude, date format, timezone string, and limit default. This far exceeds the input schema which only provides types and default, so it fully compensates for the 0% schema coverage.

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 states it returns a curated list of best objects to view for the night, which distinguishes it from siblings like get_moon_info or list_visible_planets. The verb 'Get' and resource 'curated list' are specific.

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 implies usage for nightly viewing recommendations by listing relevant parameters (lon, lat, time, time_zone). It doesn't explicitly state when not to use or mention alternatives, but the context is clear.

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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