get_zz500_stocks

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

With no annotations provided, the description carries the full burden. It discloses that the tool fetches data (read-only behavior implied) and returns either a markdown table or error message, but lacks details on rate limits, authentication needs, data freshness, or error conditions. It adds basic context but misses deeper behavioral traits.

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 and front-loaded with the core purpose, followed by specific sections for Args and Returns. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 (single optional parameter) and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose, parameter semantics, and return format. However, it lacks details on error handling or data source limitations, leaving minor gaps in contextual 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 meaningful semantics beyond the input schema: it explains that the 'date' parameter is optional, uses 'YYYY-MM-DD' format, defaults to the latest available date if None, and clarifies the parameter's purpose. With 0% schema description coverage, this fully compensates for the single parameter, providing clear usage context.

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 specific action ('Fetches') and resource ('constituent stocks of the CSI 500 Index'), distinguishing it from sibling tools like get_hs300_stocks and get_sz50_stocks that fetch different indices. It precisely defines what the tool does without being vague or tautological.

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 retrieving CSI 500 Index constituents, but does not explicitly state when to use this tool versus alternatives like get_hs300_stocks or get_sz50_stocks. No guidance on prerequisites, exclusions, or specific scenarios is provided, leaving usage context inferred rather than explicit.

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