get_us_historical_k_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the return format (Markdown table), it doesn't describe important behavioral aspects like rate limits, authentication requirements, data freshness, error conditions, or whether this is a read-only operation. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

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 sized and well-structured with clear sections for Args and Returns. The purpose statement is front-loaded, and each parameter gets a brief explanation. While efficient, the Chinese-only content might limit accessibility in some contexts, but within its language, it's concise and organized.

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's moderate complexity (5 parameters, no annotations, but with output schema), the description is minimally adequate. It covers parameters well and mentions the return format, but lacks important context about behavioral traits, usage guidelines relative to siblings, and doesn't explain what 'K-line data' specifically entails. The output schema existence reduces the need to detail return values, but other gaps remain.

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 description provides meaningful semantic information for all 5 parameters beyond what the schema offers (which has 0% description coverage). It explains that 'code' represents US stock codes with examples, clarifies date formats, indicates frequency defaults to daily, and mentions fields are optional. This compensates well for the schema's lack of descriptions, though it could provide more detail about valid frequency values or field options.

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's purpose as '获取美股历史K线数据' (Get US stock historical K-line data), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_historical_k_data' or 'get_hk_historical_k_data' that appear to handle different markets. The purpose is clear but lacks sibling differentiation.

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 multiple sibling tools for different markets (US, HK, general) and data types, there's no indication of when this specific US-focused tool is appropriate versus 'get_historical_k_data' or other market-specific variants. No usage context or exclusions are provided.

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