stock_register_kcb

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds that the tool returns a DataFrame, but does not disclose any further behavioral details such as data freshness, column schema, or errors. Thus it adds modest value 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 brief: a Chinese title, a URL, and a return annotation. While compact, it reads as unpolished fragments rather than a structured description. It earns a 4 for appropriate brevity given the zero-parameter interface.

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 no-parameter read-only tool with robust annotations, the description provides the essential return type and source URL. However, it lacks any guidance on expected columns, use cases, or relationship to other stock register tools, so it is merely adequate.

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 an empty input schema, so there is nothing for the description to meaningfully elaborate. The description's mention of return type and data source is irrelevant to parameters. Baseline 4 applies.

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 this tool returns 科创板注册制审核结果 (STAR Market registration review results) as a pandas DataFrame, distinguishing it from sibling stock_register_* tools via the explicit 科创板 (STAR Market) qualifier. However, it lacks a direct verb like 'get' or 'retrieve,' making the action implicit.

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 such as stock_register_cyb or stock_register_all_em. It only gives a data source URL and return type, with no mention of exclusions or preferred use cases.

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