get_us_sector_performance

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

No annotations are provided, so the description carries full burden for behavioral disclosure. The description mentions the return format ('Markdown格式' - Markdown format), which adds some value beyond the input schema. However, it doesn't disclose important behavioral traits like whether this is a real-time or historical data source, update frequency, data freshness, rate limits, authentication requirements, or error conditions. For a financial data tool with zero annotation coverage, this represents significant gaps.

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 appropriately concise with two brief sentences in Chinese and English. The first sentence states the purpose, and the second describes the return format. There's no wasted text or redundancy. However, the structure could be slightly improved by combining the bilingual elements more seamlessly rather than having separate language statements.

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 that the tool has an output schema (which should document return values), no parameters, and no annotations, the description provides basic purpose and format information. However, for a financial data retrieval tool with many similar siblings, the description lacks sufficient context about what 'sector performance' specifically means, timeframes covered, or data sources. The presence of an output schema reduces the need to explain return values, but more operational context would be helpful.

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 tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to explain any parameters, and it correctly doesn't attempt to do so. The baseline for 0 parameters with complete schema coverage is 4, as there's nothing to compensate for and no misleading information about parameters.

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 states '获取美股行业表现' (Get US stock sector performance), which provides a clear verb ('获取' meaning 'get' or 'retrieve') and resource ('美股行业表现' meaning 'US stock sector performance'). However, it doesn't distinguish this tool from its many siblings that also retrieve various financial data, making it somewhat vague in context. The English translation in the description ('Returns: Markdown格式的行业表现数据') adds some clarification but doesn't fully differentiate purpose.

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 provides no guidance on when to use this tool versus alternatives. With 50+ sibling tools retrieving various financial data (e.g., get_us_market_indices, get_us_stock_realtime_data, get_stock_industry), there's no indication of when this specific sector performance tool is appropriate versus other market data tools. The description lacks any context about use cases, prerequisites, or exclusions.

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