amac_securities_info

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

The annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, which cover the safety profile. The description adds the source URL and the pandas.DataFrame return type, which is helpful but does not disclose any additional behavioral traits such as pagination, update frequency, network dependency, or potential errors. This adds some context beyond annotations but is not rich.

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, packing the source, exact disclosure type, URL, and return type into one short block. There is no fluff, but the formatting is a single dense paragraph with docstring syntax, which could be slightly more readable if broken into sentences or lines. Still, every piece of information serves a purpose.

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?

Given that the tool has no parameters, no output schema, and strong annotations, the description is largely complete: it names the exact data set, the source institution, and the return type. Missing details like whether the DataFrame covers all products or only current ones would be nice, but for a simple read-only lookup tool, the provided context is 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 accepts zero parameters, and the input schema is empty with 100% schema description coverage. According to the rubric, a zero-parameter tool gets a baseline of 4. The description correctly notes the return type but does not need to explain parameters, so the baseline 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 identifies the tool's scope: it returns AMAC's disclosure of securities companies' collective asset management products (证券公司集合资管产品公示). The name and URL further confirm the resource, and the specific product type distinguishes it from other AMAC tools. However, it lacks an explicit verb (e.g., 'retrieve' or 'list'), instead framing everything as a noun phrase, so it falls just short of a 5.

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?

Usage context is implied by the explicit product type: if an agent needs securities company collective asset management product disclosures from AMAC, this is the tool. But there is no explicit statement about when to use this versus the many other amac_* sibling tools, nor any mention of exclusions, prerequisites, or alternative tools.

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