A股大宗交易

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It mentions the data fields returned (price, volume, premium rate) but provides no information on authentication, rate limits, pagination, or potential side effects. For a read operation, this minimal transparency is insufficient.

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 concise (two sentences) and front-loaded with the core purpose. Every sentence serves a clear role: stating the data provided and its significance. No redundant or unnecessary information, making it efficient for an AI agent 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?

For a simple tool with two optional parameters and no output schema, the description sufficiently covers the main purpose and key data points. However, it lacks details on output format, real-time vs. historical nature, and the effect of the 'limit' parameter. Still, it is mostly complete given the tool's simplicity.

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 100% coverage: both 'symbol' and 'limit' are described with defaults and explanations. The description adds context about the data contents (e.g., premium rate) but does not elaborate on parameter behavior (e.g., how symbol filtering works or how limit interacts with output). Given high schema coverage, the description meets the baseline without adding substantial param-specific value.

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 retrieves A-share block trade data including price, volume, and premium rate, and explains its significance for institutional trading. The verb '获取' (get) and resource are specific, and it differentiates itself among sibling tools by focusing on a unique data type (大宗交易).

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 implies usage for obtaining block trade data but does not explicitly state when to use this tool versus alternatives like stock_realtime or stock_fund_flow. There is no guidance on prerequisites, context, or exclusions, leaving the agent to infer usage from the tool's name and description alone.

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