get_korea_weather
Get Korean weather conditions and forecasts.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | ||
| type | No |
kdata-gate
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully carries the burden of behavioral disclosure. It only states it 'gets' data but omits any details about side effects, data freshness, rate limits, or required permissions. Minimal transparency.
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 a single, front-loaded sentence with no extraneous words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema and the minimal parameter info, the description lacks completeness. It does not explain the output format, possible values for 'type', or how to specify cities. More context is needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has two parameters ('city', 'type') with 0% description coverage, and the tool description adds no explanation of their meaning, allowed values, or defaults. The agent has no guidance on how to fill these parameters correctly.
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 action ('Get') and the resource ('Korean weather conditions and forecasts'). It distinguishes this tool from all siblings, which cover different domains like stocks, real estate, etc. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, or any prerequisites. The agent must infer usage solely from the tool's name and context. This lack of explicit guidance reduces usability.
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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TDQS
C2.9/5.0
Disambiguation4/5
Most tools have distinct purposes, but create_buy_ship_cart_order and create_direct_buy_ship_order are nearly identical, causing potential confusion. Additionally, build_buyer_discovery_queue and build_cash_sprint_packet overlap in targeting buyer segments.
Naming Consistency5/5
All tools follow a clear verb_noun pattern (build_, get_, create_, search_) with consistent snake_case, making it easy to infer functionality from the name.
Tool Count3/5
With 26 tools covering diverse domains (stock market, real estate, tourism, sourcing, etc.), the scope feels broad and somewhat bloated. A more focused set would improve coherence.
Completeness3/5
The tool set covers many aspects of Korea data and seller workflows, but notable gaps exist: no tools for actual listing posting, sending communications, or completing transactions, as many build_ tools explicitly exclude those steps.