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weather-history

Get historical daily weather data (temperature, precipitation, wind, sunshine) for any location from 1940 to recent days. Use for seasonal analysis, anomaly detection, and climate-context enrichment.

Instructions

Historical daily weather (temperature, precipitation, wind, sunshine) for any location from 1940 to ~5 days ago. Uses ERA5 reanalysis data. Accepts city name or lat,lng. Returns per-day values plus period summary stats. Useful for seasonal analysis, anomaly detection, and climate-context enrichment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationNoCity name (e.g. 'Phoenix, AZ') or 'lat,lng' (e.g. '33.45,-112.07'). Defaults to 'New York, NY'.
start_dateNoStart date YYYY-MM-DD (e.g. 2024-01-01). Earliest: 1940-01-01. Defaults to 30 days ago.
end_dateNoEnd date YYYY-MM-DD (latest: ~5 days before today). Defaults to yesterday if omitted.
varsNoComma-separated variable names to include. Defaults to temperature_2m_max, temperature_2m_min, temperature_2m_mean, precipitation_sum, wind_speed_10m_max, sunshine_duration. Valid options: apparent_temperature_max, apparent_temperature_mean, apparent_temperature_min, cloud_cover_mean, et0_fao_evapotranspiration, precipitation_hours, precipitation_sum, rain_sum, shortwave_radiation_sum, snowfall_sum, sunshine_duration, temperature_2m_max, temperature_2m_mean, temperature_2m_min, weather_code, wind_direction_10m_dominant, wind_gusts_10m_max, wind_speed_10m_max
unitsNoUnit system. 'metric' = °C / mm / km/h (default). 'imperial' = °F / inch / mph.
Behavior4/5

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

With no annotations, the description fully covers behavioral traits: it's a read-only data retrieval tool, uses ERA5 reanalysis, has a known date range (1940 to ~5 days ago), and accepts city name or lat/lng. It does not explicitly state it is read-only or mention rate limits, but these are not critical for a historical data tool.

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?

Description is three sentences: first defines core function, second specifies input format and data range, third clarifies output and use cases. No redundant information, front-loaded with key facts.

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 no output schema, the description adequately explains the tool's return: per-day values plus period summary stats. It covers data source, time range, input options, and use cases, making it complete for an agent to decide whether to invoke this tool.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining that location accepts city name or lat/lng, that units are metric/imperial, and that vars defaults to a set of common variables. This context helps agents understand parameter usage beyond the schema descriptions.

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?

Description clearly states tool provides historical daily weather data from 1940 to ~5 days ago, using ERA5 reanalysis. It specifies the data types (temperature, precipitation, wind, sunshine) and explicitly contrasts with sibling tools like 'weather' (current conditions) and 'aviation-weather' (aviation-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?

Description explicitly lists use cases (seasonal analysis, anomaly detection, climate-context enrichment) and implies when not to use (e.g., for current weather, use 'weather' tool). However, it does not explicitly exclude other tools or provide alternative names.

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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