index_ci_cx

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds only the return type (pandas.DataFrame) and a data source URL, but does not mention network dependencies, update frequency, or any other behavioral traits. It neither contradicts nor significantly enriches beyond annotations.

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 extremely concise and well-structured, containing only three lines: the title, the URL, and the return type/format. Every part adds value without redundancy. This is an appropriate size for a zero-parameter read-only tool.

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 parameterless read-only tool, the description is moderately complete. It identifies the data source, provides a reference URL, and the return type. However, it lacks detail about the DataFrame's columns, index, units, or the period covered, which could be important for an agent to assess the data's relevance. Since no output schema exists, the description carries the full burden for return-value semantics.

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 accepts zero parameters, so the baseline score is 4. The description adds no parameter information (there is nothing to describe), which is acceptable given the empty schema. No additional semantics are needed.

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 '财新数据-指数报告-资本投入指数' (Caixin Data – Index Report – Capital Input Index), clearly identifying the resource. The return type 'pandas.DataFrame' and URL reinforce that this tool provides capital input index data. It doesn't explicitly distinguish itself from sibling Caixin index tools like index_nei_cx, but the name and description are specific enough.

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 given on when to use this tool versus alternatives such as index_nei_cx or other index_*_cx tools. There are no explicit usage conditions, exclusions, or context on when this index is relevant. The usage is only implied by the resource name.

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