index_ii_cx

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

Annotations already declare the tool read-only and idempotent, so the safety profile is covered. However, the description only adds the source URL and return type, with no additional behavioral context like network dependencies, data limits, or error conditions, which is a notable gap for a data-fetching 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, but its structure is a terse Python docstring format. It lacks a clear, human-readable summary and omits potentially useful details, yet it contains no unnecessary words.

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?

With no output schema and no parameters, the description should clarify what the returned DataFrame contains. It merely repeats the title '产业指数' and gives a type, leaving column details, data meaning, and update frequency ambiguous. This is inadequate for an agent to reliably interpret the result.

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, making schema coverage trivially 100%. The description does not need to explain parameter semantics, and no parameter information is missing.

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 names the specific resource '产业指数' (industry index) from 财新数据 and specifies the return type as pandas.DataFrame, indicating a clear data retrieval function. However, it lacks an explicit verb and does not differentiate itself from sibling index tools beyond the name.

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 such as index_dei_cx or other index-related tools. There is no mention of data coverage, frequency, or any prerequisites, leaving the agent uninformed about selection criteria.

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