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Stellarhound — stargazing forecasts, dark-sky sites & aurora

get_tonight_agenda

Read-only

Get tonight's stargazing plan for a location: score, darkness window, and what to observe.

Use when the user asks "what can I see tonight" / "is tonight worth going
out". Returns tonight's sky score and darkness window plus a ranked agenda
of observing targets appropriate for the location's sky darkness.

Args:
    lat: Latitude in decimal degrees (-90..90).
    lon: Longitude in decimal degrees (-180..180).

Returns {timezone, light_pollution, tonight:{date, darkness, weather,...},
targets/agenda entries, attribution}. Report as returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read. The description adds context about returning a ranked agenda and 'report as returned' but does not detail aspects like network calls, timezone handling, or any limitations. With good annotations, a 3 is appropriate, adding some value beyond annotations.

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?

The description is compact and well-structured, with a brief summary, usage context, args, and return format. Each section adds value. It could be slightly more concise but is not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 2 simple params, no output schema, and annotations cover safety, the description provides a clear return structure including the fields returned. It adequately explains the input and high-level output, but it does not elaborate on the 'weather' or 'darkness' fields or the agenda possibilities, leaving some ambiguity for a tool that returns complex structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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

Schema has 0% description coverage, but the description provides clear meaning for lat and lon ('Latitude in decimal degrees (-90..90)') and 'Longitude in decimal degrees (-180..180)'. This goes beyond the schema, which only names them. Given only two simple params, this is adequate, though it doesn't add additional format details beyond 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?

The description uses a specific verb ('Get'), a clear resource ('tonight's stargazing plan'), and includes the key elements: sky score, darkness window, and observing targets. It distinguishes from siblings by focusing on the 'tonight' agenda for a location, but it does not explicitly differentiate from similar siblings like get_stargazing_conditions.

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

Usage Guidelines5/5

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

Explicitly states when to use: when the user asks 'what can I see tonight' or 'is tonight worth going out'. This clearly differentiates from siblings, which likely focus on broader conditions or forecasts. No exclusions provided but context is sufficient.

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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