fund_individual_profit_probability_xq

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds context by specifying the return type (pandas.DataFrame) and the meaning of the output (profit probability Y%), which goes beyond the annotations. No contradictions found.

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 somewhat scattered, mixing a Chinese summary, an example API URL, and parameter documentation. It is concise in length but lacks a clear, structured layout. Each part contributes some value, but the organization could be improved for readability.

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?

For a simple two-parameter tool with no output schema, the description covers the key aspects: purpose, parameters, return type, and source. It does not detail the exact format of the returned DataFrame, but given the tool's simplicity and the presence of annotations, the information is largely sufficient for an agent to invoke it correctly.

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%, but the description documents both parameters: symbol is 基金代码 (fund code) and timeout is 'choice of None or a positive float number'. This provides meaningful semantics beyond the schema's type/default definitions. However, it does not elaborate on the DataFrame structure or further constraints on timeout.

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's function: it computes the profit probability of a fund when bought at any historical point and held for X years. The specific metric (盈利概率), source (雪球基金), and scenario (历史任意时点买入，持有满 X 年) are explicit, distinguishing it from sibling fund tools like basic info or analysis.

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 implies the use case (querying fund profit probability) but does not explicitly mention when to use this tool over alternatives or provide exclusions. Sibling tools exist (e.g., fund_individual_basic_info_xq), but no comparison is given. Usage context is present but not fully articulated.

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