stock_ipo_tutor_em

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

Annotations cover readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the source URL and return type but does not disclose other behavioral traits like data scope, freshness, rate limits, or any quirks of the returned DataFrame. This is adequate for a simple read-only tool but lacks depth.

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 concise, consisting of a source title, URL, and return type in a docstring-like format. It has no fluff, but it repeats the title from annotations and does not provide a structured narrative for an AI agent, so it is not maximally effective.

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, the description should clarify what the returned DataFrame contains. It only repeats 'IPO辅导信息' without specifying columns, update frequency, or data scope. For an agent to use the data meaningfully, it needs more detail about the return structure and content limits.

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 the schema is trivially complete (100% coverage). Since there are no parameters to describe, the baseline of 4 applies; the description does not need to compensate for any parameter documentation gaps.

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 identifies the data source ('东方财富网-数据中心-新股数据-IPO辅导信息'), the URL, and the return type ('IPO辅导信息', pandas.DataFrame). This makes the purpose clear for a data-fetching tool, though it relies on the same terminology as the tool name and title rather than a distinct verb phrase.

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 compared to sibling tools. It only states the source and return type, with no context about selection criteria, alternatives, or preconditions.

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