search_us_stocks

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format (Markdown) but doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what constitutes a 'search' (e.g., fuzzy matching, exact matches). This is inadequate for a tool with no annotation coverage.

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 front-loaded with the core purpose. The Args/Returns structure is clear, though the use of Chinese text might reduce accessibility for some agents. There's no wasted verbiage, but the formatting could be more polished.

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 has an output schema (which should document return values) and only one parameter, the description is minimally complete. However, with no annotations and sibling tools present, it fails to provide sufficient context about behavioral traits and usage differentiation, making it only adequate for basic understanding.

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 adds minimal value beyond the input schema. It clarifies that the 'keyword' parameter accepts stock names or codes, which is useful since schema coverage is 0%. However, it doesn't provide examples, format constraints, or guidance on how the search operates (e.g., partial matches, case sensitivity), leaving gaps in understanding.

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 searches for US stocks using keywords (stock names or codes), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from its sibling 'search_hk_stocks' beyond the 'US' qualifier in the name, missing an opportunity to clarify the regional distinction.

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?

No guidance is provided on when to use this tool versus alternatives like 'get_us_stock_basic_info' or 'search_hk_stocks'. The description lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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