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IBM

chuk-mcp-open-meteo

by IBM

batch_get_marine_forecasts

Retrieve marine forecasts for multiple coastal locations in one request. Compare wave heights and conditions across surf spots or along a coastline.

Instructions

Get marine forecasts for multiple coastal locations in a single API call.

This tool uses Open-Meteo's native batch support to fetch marine conditions for many locations at once. Useful for comparing surf spots, planning coastal trips, or monitoring conditions along a coastline.

Args: latitudes: Comma-separated latitude values for all locations. Example: "21.31,33.87,36.97" (Honolulu, San Diego, Monterey) Must be over ocean/coastal areas. Same count as longitudes. longitudes: Comma-separated longitude values for all locations. Example: "-157.86,-118.29,-122.00" Must be over ocean/coastal areas. Same count as latitudes. timezone: Timezone name or "auto" for automatic detection per location hourly: Comma-separated hourly marine variables. If not provided, defaults to: wave_height, wave_direction, wave_period, wind_wave_height, swell_wave_height, sea_level_height_msl daily: Comma-separated daily marine variables (e.g., wave_height_max, wave_direction_dominant) forecast_days: Number of forecast days (1-16). Default is 7.

Returns: BatchMarineForecastResponse: Contains: - results: List of BatchMarineForecastItem, each with location_index and forecast - total_locations: Number of locations queried

Tips for LLMs: - Use batch_geocode_locations first to get coordinates for coastal cities - Results are in the SAME ORDER as the input coordinates - Useful for "compare surf conditions" or "wave heights along the coast" queries - All locations share the same hourly/daily variables and forecast_days - Coordinates must be over ocean/coastal areas (inland locations will fail)

Example: # Compare surf conditions at 3 beaches result = await batch_get_marine_forecasts( latitudes="21.31,33.87,36.97", longitudes="-157.86,-118.29,-122.00", hourly="wave_height,wave_period,swell_wave_height", forecast_days=3 ) for item in result.results: waves = item.forecast.hourly.wave_height[0] print(f"Location {item.location_index}: {waves}m waves")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dailyNo
hourlyNo
timezoneNoauto
latitudesYes
longitudesYes
forecast_daysNo
Behavior5/5

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

No annotations exist, yet description fully discloses behavior: requires ocean coordinates, shares variables among locations, returns ordered results, uses Open-Meteo batch support, and explains default variable selection. Covers what to expect and what fails.

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?

Well-structured with intro, args, returns, tips, and example. Length is justified by complexity; no fluff. Slightly verbose with code example but adds clarity.

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?

Covers all necessary aspects: purpose, parameters, return format, constraints, usage tips, and example. No output schema, but return type is described sufficiently. Complete for a batch tool with 6 parameters.

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?

Schema has 0% coverage, but description provides exhaustive parameter details: formats (comma-separated), examples, defaults, constraints (forecast_days 1-16, timezone 'auto'). Goes well beyond schema to explain usage.

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?

Clearly states it fetches marine forecasts for multiple coastal locations via batch API. Distinguishes from single-location get_marine_forecast and other batch tools like batch_get_weather_forecasts.

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 specific use cases (comparing surf spots, coastal trip planning) and tips (use batch_geocode_locations first, results in order, coordinates must be over ocean). Lacks explicit 'when not to use' but context is clear from sibling tools.

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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