rank_etf_return

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

With no annotations provided, the description carries the full burden of disclosing behavior. It explains how endpoints are resolved to trading days, how missing prices are reported in `excluded` rather than dropped, and the effect of the `worst` flag. This goes beyond basic expectations and provides significant behavioral insight, though it does not mention aspects like pagination or rate limits.

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, starting with a concise purpose statement and then a clean Args list. Each parameter line is compact and informative, with examples where helpful. There is no redundant or irrelevant content; every sentence earns its place.

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 complexity of 13 optional parameters and the existence of an output schema, the description provides all necessary context: the tool's purpose, filter options, behavioral nuances (missing data handling, worst flag), and parameter semantics. Since the output schema exists, it does not need to detail the return structure, making this description effectively complete for an agent.

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 0% description coverage, but the description compensates by listing all 13 parameters with short, meaningful explanations and examples (e.g., 'query: Name substring filter, e.g. "채권혼합"'). This fully adds semantic value beyond the raw schema properties, which contain no descriptions.

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 opens with 'Rank ETFs by price return over a period', which clearly states the specific action and resource. This distinguishes it from siblings like compare_etf (which compares specific ETFs) and get_etf_history (which provides historical data). The optional filter set further clarifies the scope.

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 clearly states the tool's use case: ranking ETFs by return with optional filters. It does not explicitly mention when not to use it or name alternatives, but the purpose is unambiguous enough for an agent to select it when a ranked list is needed. The context is clear, though exclusions are not explicitly stated.

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