PER·PBR·ROE 순위 조회 (시장 전체)

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 key behavioral traits: it can only sort by one criterion at a time, cannot combine indicators, and must be called multiple times for combined filters. It also mentions the underlying API code (키움 ka10026) and confirms this is the only valuation scanning tool. Though it doesn't describe the return format, the read-only nature is clearly implied.

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 efficient: four sentences, each serving a distinct purpose—core function, limitation/workaround, usage patterns, and differentiation from alternatives. No fluff or redundant repetition of schema details. Well-structured and easy to parse.

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 there is no output schema and no annotations, the description covers purpose, usage, limitations, and alternatives thoroughly. It falls short of describing the output structure (e.g., what fields the returned list contains), but for a straightforward query tool this is a minor gap. The guidance on when to use which metric and the combination workaround makes it robust for agent decision-making.

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?

Schema coverage is 100% (both top and metric have descriptions). The description adds value beyond the schema by explaining the strategic meaning of each metric (low PER/PBR for value, high ROE for efficiency, high PBR/low ROE for overheating) and the top parameter's default and max are already in the schema. This semantic guidance helps the agent choose appropriate metrics.

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 the tool sorts the entire market by one of PER/PBR/ROE and returns the top 100 stocks (e.g., '시장 전체를 PER·PBR·ROE 중 한 가지 기준으로 줄 세운 상위 100종목을 조회합니다'). It uses specific verbs and resources, and explicitly differentiates from get_ranking and get_stock_price by noting this is the only tool for market-wide valuation scanning.

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?

Provides explicit usage context: when to use this tool (value screening with low PER/PBR, capital efficiency with high ROE, overheating/insolvency checks with high PBR/low ROE), and when not to use it (volume/price-change rankings → get_ranking, single-stock PER/PBR → get_stock_price). Also explains the limitation of not combining metrics and the workaround of calling twice.

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