get_forecast_report

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that reports are not always required, hinting at potential empty results, but does not cover other critical aspects such as authentication needs, rate limits, error handling, or whether this is a read-only operation. The description is too sparse for a tool with no annotation support.

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 well-structured and front-loaded with the core purpose, followed by a note on limitations, and then clear sections for Args and Returns. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 the tool's moderate complexity (3 parameters, no annotations, but has an output schema), the description is reasonably complete. It covers the purpose, parameter semantics, and return format (Markdown table or error message). The output schema existence means the description doesn't need to detail return values, but it could improve by addressing behavioral aspects like error conditions or data freshness.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'code' is a stock code with an example ('sh.600000'), and clarifies that start_date and end_date are for 'report publication/update' in 'YYYY-MM-DD' format. This compensates well for the schema's lack of descriptions, though it could provide more context on valid date ranges or code formats.

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 the tool 'fetches performance forecast reports (业绩预告) for a stock within a date range,' specifying the verb (fetches), resource (performance forecast reports), and scope (stock, date range). It distinguishes from siblings by focusing on forecast reports rather than other financial data types like balance sheets or historical prices.

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 some implied usage context by noting 'Companies are not required to publish these except in specific cases,' which suggests this tool may return empty results. However, it lacks explicit guidance on when to use this tool versus alternatives like get_performance_express_report or other financial data tools, and does not mention prerequisites or exclusions.

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