stock_new_a_spot_em

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the source URL and return type (pandas.DataFrame), which is useful but minimal. It doesn't describe potential failure modes, rate limits, or whether the data is from a live feed. With annotations covering the safety profile, a 3 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 concise, consisting of a title, URL, and return type in a structured format. Each line serves a purpose: identifying the quote source, providing the source URL, and specifying the return type. It is appropriately sized for a zero-parameter tool and is front-loaded with the core purpose. Not overly verbose, though the URL is somewhat extraneous.

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?

The tool has no output schema, so the description must convey what the tool returns. It says '实时行情' and rtype pandas.DataFrame, but it doesn't specify the data columns or the exact scope (e.g., all new A-shares on a specific exchange). The garbled text and lack of context about the data content make it incomplete. However, for a simple no-parameter tool, it's minimally 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 0 parameters, so the schema fully describes the input. The description adds no parameter-specific semantics, but with no parameters, the baseline of 4 applies. The URL might hint at the data source, but it is not a parameter explanation. No compensation 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 '东方财富网-新��-实时行情' which indicates real-time quotes for new shares from East Money, and the title annotation confirms '新股' (new shares). This is a clear verb+resource, but the garbled character and lack of explicit mention of 'A-shares' (though implied by the name) prevents a perfect score. It doesn't explicitly distinguish from sibling tools like stock_cy_a_spot_em or stock_sh_a_spot_em, but the '新股' wording provides some differentiation.

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. There is no mention of use cases, prerequisites, or exclusions. The URL is the only context, but it doesn't explain when this tool is the appropriate choice among the many stock spot tools. This is a clear gap.

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