메리츠 해외주식 시세

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: all operations are GET requests, and api_type='describe' returns parameter descriptions dynamically. It does not mention auth or rate limits, but given the annotation coverage this is acceptable.

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 well-structured: a short usage instruction followed by a compact endpoint table. Each line earns its place by mapping an api_type to a data type. The opening phrase slightly duplicates the title but is not harmful. Overall it is efficient and scannable.

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?

Given the tool is a multi-endpoint dispatcher with opaque params, the description is not fully self-sufficient for direct invocation of each sub-API. It mitigates this by pointing to api_type='describe' for parameter details, and an output schema exists. Still, for an agent to call, say, ovs_market_candles_days correctly, it would need an extra describe round-trip; the static description alone lacks that detail.

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?

Input schema has 0% description coverage, so the description must compensate. It adds meaning by listing valid api_type values and explaining that params should contain API parameters. However, it does not describe the actual keys or structures for the params object, relying instead on the api_type='describe' mechanism as a runtime fallback. This is partial compensation but not full parameter documentation.

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 states this tool provides overseas stock market quotes ('해외주식 시세') and enumerates six distinct endpoint variants with specific purposes such as daily candles, minute candles, orderbook, current price, and trades. This makes the tool's function obvious and differentiates it from sibling tools like meritz_market.

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 tells the agent how to select an API via api_type and provides a table mapping each api_type value to its data purpose. It also instructs to call api_type='describe' for parameter explanations. It does not explicitly discuss when to prefer this tool over meritz_market or meritz_forex, but the overseas-market scope is clear from the title and description.

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