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get_weather_alerts

Retrieve active extreme weather alerts for Indonesia, including heavy rain and thunderstorm warnings at district level using Common Alerting Protocol data.

Instructions

Mengambil peringatan dini cuaca ekstrem (hujan lebat/petir) yang sedang aktif di Indonesia.
Data berbasis Common Alerting Protocol (CAP) hingga level kecamatan.

Args:
    language: Bahasa output, "id" untuk Indonesia atau "en" untuk English (default: "id")

Returns:
    Daftar peringatan dini cuaca aktif dengan informasi provinsi terdampak,
    waktu publikasi, deskripsi wilayah, dan tautan detail CAP.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoid

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the data source (CAP-based), geographic granularity (kecamatan level), and return format (list with province, time, area description, CAP links). However, it does not mention rate limits, authentication needs, or potential errors, leaving some behavioral gaps.

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 efficiently structured with three sentences: purpose, parameter details, and return information. Each sentence adds value without redundancy, and it is front-loaded with the core functionality.

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

Completeness4/5

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

Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is mostly complete. It covers purpose, parameter semantics, and return content. However, it could improve by addressing potential limitations or error cases, though the output schema may handle return values.

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?

The input schema has 0% description coverage, but the description compensates by explaining the 'language' parameter's purpose, options ('id' or 'en'), and default value. Since there is only one parameter, this provides adequate semantic context beyond the schema's basic structure.

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 the specific action ('Mengambil peringatan dini cuaca ekstrem') and resource ('di Indonesia'), with precise scope ('yang sedang aktif', 'berbasis Common Alerting Protocol (CAP) hingga level kecamatan'). It distinguishes from siblings by focusing on active weather alerts rather than forecasts, earthquakes, or detailed searches.

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 retrieving active extreme weather alerts in Indonesia, but does not explicitly state when to use this tool versus alternatives like 'get_weather_forecast' or 'search_weather_alerts_by_kecamatan'. It provides clear context but lacks explicit exclusions or named alternatives.

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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