Earnings Ann

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

No annotations are provided, so the description carries the full behavioral burden and does so well: it defines an output contract (only real interface entries, empty list rather than fabrication when no forecasts exist, no premature interpretation of profit ranges), and states the factual-only/no-recommendation boundary. It omits auth, rate-limit, and pagination behavior, keeping it below a 5.

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?

Front-loaded with the tool's purpose, then the filter logic, then the output contract. It is slightly dense with skill-mapping and contract boilerplate, but each sentence carries a distinct constraint rather than padding.

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?

An output schema exists, so return values need not be re-explained, and the description nonetheless pins down the output contract and scope limits well. The only real gap is the unexplained 'code' and 'page_size' parameters for a tool that accepts user input.

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?

Schema description coverage is 0%, so the description must explain the parameters, but it never addresses either 'code' or 'page_size'. The title-keyword filtering it describes is baked into the tool logic, not a parameter, so the two actual inputs remain undocumented in both schema and description.

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?

States a specific verb and resource: scanning the announcement list for titles containing the earnings-forecast keywords (业绩预告/业绩快报/业绩预告修正), and names the exact fields returned (art_code/title/date). It also explicitly differentiates from the sibling ann_content ('正文用 ann_content 另取'), so an agent can tell the two apart without opening either schema.

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?

Clearly signals the use case (scanning for earnings previews/flash reports) and routes body-text extraction to ann_content, which is the complementary tool. It lacks an explicit 'when not to use' clause or a reference to ann_list as the general-purpose alternative, so it is strong context but not full routing guidance.

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