spot_symbol_table_sge

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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds the source URL and the return type (pandas DataFrame), which is useful context, but it does not disclose any additional behavioral traits such as pagination, rate limits, or error behavior. This meets the baseline for a simple read-only tool.

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 very short and to the point, containing only a title, source URL, and return type. There is no wasted text, and the key information is immediately visible, making it appropriately concise and well-structured.

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 zero-parameter read-only tool, the description adequately conveys that it returns a pandas DataFrame containing the SGE variety table and provides the data source URL. While it does not enumerate the columns or describe the table structure in detail, the name and context make the purpose sufficiently clear.

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 zero parameters and the input schema is an empty object, so there are no parameter semantics to explain. The description is not required to compensate for any schema gaps, meriting the baseline score of 4.

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 fetches the variety table (品种表) from the Shanghai Gold Exchange (SGE) market data section, identifying a specific resource and returning a pandas DataFrame. However, it does not explicitly differentiate this from other SGE-related tools like spot_quotations_sge or spot_hist_sge, so it falls short of a 5.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no explicit exclusion criteria. The description simply states what it returns, leaving the agent to infer the appropriate use case on its own.

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