fund_fh_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful behavioral details such as page=-1 meaning 'fetch all pages' and the sorting options, but does not describe potential quirks like rate limits or error handling. The added value is moderate.

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 a well-structured docstring with a title, a source URL, parameter definitions, and return type. The long enum lists for typ and rank are necessary given the missing schema descriptions, and the content is free of fluff. It is slightly dense but earns its place.

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 there is no output schema, the description covers the essentials: source (URL), all parameters with meanings and defaults, and return type (pandas.DataFrame). It does not discuss edge cases or result size expectations, but for a read-only query tool with strong annotations, this is nearly complete.

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 input schema has 0% description coverage, leaving the description as the sole source of meaning. The description fully documents all five parameters, including enum choices for typ and rank, with explicit explanations for each rank value (e.g., BZDM=基金代码, DJR=权益登记日). This is exemplary compensation for an otherwise bare schema.

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 tool as '天天基金网-基金数据-分红送配-基金分红' and includes the source URL, making it clear this queries fund dividend data from Eastmoney. However, it lacks an explicit verb like 'query' or 'fetch', and the distinction from closely related siblings (e.g., fund_announcement_dividend_em) is not explicitly stated.

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. It does not mention any exclusions or preferred use cases, leaving the agent to infer from the name and URL. This is a clear gap given the large family of fund-related tools.

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