index_stock_info

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

Annotations already cover the safety profile (readOnlyHint, openWorldHint, idempotentHint, destructiveHint). The description adds the data source (JoinQuant) and return type (DataFrame), which is useful but does not disclose additional behavioral traits such as pagination, rate limits, or data freshness. This is consistent with annotations and adds some value, so a mid-range score is appropriate.

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, consisting of the title, a reference URL, and return type annotations. It is compact and free of fluff, but it lacks a clearer structure or a sentence explaining the tool's action. Still, every line serves a purpose, so it earns a high score for conciseness.

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 tool, the description gives a basic understanding: it returns a DataFrame of index information. However, it does not specify the columns or confirm the exact output structure, and there is no output schema to fill the gap. The URL might provide details, but it is not self-contained. This is adequate but leaves clear gaps.

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, so the input schema is trivially complete (100% coverage). The description does not need to explain parameter behavior. Per the rubric, a zero-parameter tool gets a baseline score of 4, and no deduction is needed since there are no parameters to document.

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 states it returns an '指数列表' (index list) from JoinQuant, indicating a tool that retrieves a list of index information. This distinguishes it from sibling tools like index_hist_cni (historical data) or index_stock_cons (constituents). However, there is no explicit verb like 'get' or 'list', so it falls short of a fully specific verb+resource+scope description.

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. It does not mention any scenarios, prerequisites, exclusions, or alternative tools. The only extra context is a URL to the JoinQuant data dictionary, which is a reference link rather than usage guidance.

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