get_us_market

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

Beyond the annotations, the description discloses a crucial behavioral trait: the returned fields are not fixed and depend on the upstream source. It provides an observed field list, warns against filling missing indices from learned knowledge, and clarifies that values are a current snapshot. This is valuable context that annotations alone do not provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but every sentence earns its place: definition, usage triggers, variability warning, observed fields, no-fabrication rule, snapshot clarification, and alternative tool. The caveats are front-loaded and immediately relevant.

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

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

With no parameters, strong annotations, an output schema available, and direct guidance on return variability and alternatives, the description fully equips an agent to select and invoke the tool correctly. Nothing critical is missing.

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

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

The input schema has zero parameters, so there is no parameter semantic burden. The description still adds useful intent-level context by listing natural-language queries that map to this tool, but it does not need to explain parameter meanings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool as a US market snapshot covering major indices, VIX, and gold. It uses specific verbs and a concrete scope, and the examples ('미국 시장 어때', 'VIX 얼마', '금값') make the resource unmistakable. It also implicitly distinguishes itself from siblings like get_us_chart by emphasizing 'current snapshot'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states which kinds of questions to use it for and gives a concrete alternative: if historical returns are needed, use get_us_chart. This gives an agent clear routing guidance rather than leaving the choice to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.