Sunshine Atlas

Find sunny destinations

find_sunny_destinations

Ranked answer to "where is it sunny (and warm) in ?" — destinations sorted by that month's 0–100 Sunshine Score (long-term climate normals). Filter by continent or country, minimum daytime temperature, population, swimmable sea (≥21°C), or a ceiling on the midday UV index. Every result carries that month's temperatures, rain, midday UV (WHO scale) and sea temperature, plus a citable destinationsmap.com URL.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	How many results (default 10, max 50)
`month`	Yes	Month name ("November", "nov") or number 1–12
`where`	No	Optional continent ("Europe", "Asia", "North America", …) or country (name or ISO-2 code) to search within. "Europe" uses the traveler definition and includes the Canary Islands.
`max_midday_uv`	No	Only places whose typical midday UV index that month is at or below this (WHO scale: ≤2 low, ≤5 moderate, ≤7 high). For sun-sensitive travellers — "sunny but not fierce".
`min_day_high_c`	No	Only places at least this warm by day that month, °C
`min_population`	No	Only places with at least this population (default 0 = include small islands and outposts)
`require_swimmable_sea`	No	Only coastal places with sea ≥21°C that month

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedJul 29, 2026

addedInput schema / properties / max_midday_uv

Added value: +{
+  "description": "Only places whose typical midday UV index that month is at or below this (WHO scale: ≤2 low, ≤5 moderate, ≤7 high). For sun-sensitive travellers — \"sunny but not fierce\".",
+  "type": "number"
+}

First observedJul 12, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does well: it states that results are ranked, sorted by climate normals, filterable, and that each result includes temperatures, rain, UV, sea temperature, and a URL. It does not explicitly state that the operation is read-only or mention potential data caveats, but it strongly implies a non-destructive lookup.

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 dense yet efficient: it front-loads the ranked-answer behavior in the first sentence, groups filter capabilities in the second, and specifies output contents in the third. Every sentence adds distinct information, with no filler or repetition.

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?

The tool has no output schema, but the description explicitly enumerates what every result carries, including month-specific temperatures, rain, UV, sea temperature, and a citable URL. Combined with fully described parameters Jew and no required alternative routing, an agent has enough context to call it correctly.

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 description coverage is 100%, so the baseline is 3. The description summarizes the filter dimensions (continent/country, min temperature, population, swimmable sea, UV ceiling) but adds no meaning beyond what the schema property descriptions already offer. It does not compensate beyond that baseline.

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 names a specific verb ('find'), a concrete resource ('sunny destinations'), and the exact ranking logic (0–100 Sunshine Score for the requested month). It clearly distinguishes itself from siblings like compare_destinations and get_destination_climate by framing itself as a ranked list answer to a 'where is it sunny?' query.

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 gives clear context for the query type this tool answers and lists available filters, so an agent can tell when this tool is appropriate. It does not explicitly name alternatives or say when not to use it (e.g., when a direct climate comparison is needed), so it stops short of a 5.

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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