option_value_analysis_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which cover safety and idempotency. The description adds the return type (pandas.DataFrame) and the source URL, providing some behavioral context. However, it does not disclose further behavioral details such as data update frequency, limitations, or potential large response sizes. This is acceptable given the annotations but adds only marginal value.

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: a title, URL, return type, and return format. It is well-structured and contains no unnecessary words. Every component serves a purpose, making it easy for an agent to quickly parse the essential information.

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 simplicity (no parameters), strong safety annotations, and the presence of a return type, the description covers the essential facts: what it is, where the data comes from, and what it returns. It does not detail the exact columns or data semantics, but for a no-parameter read-only data retrieval tool, this is sufficient. The output schema is absent, so the return type mention helps fill that gap.

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 has zero parameters, so the input schema fully defines the call interface. The description does not need to explain any parameters, and with 100% schema coverage, the baseline for parameter semantics is 4. The description adds no parameter-related info, which is fine.

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 providing '期权价值分析' (option value analysis) from a specific source (东方财富网) and includes the URL. This clearly indicates the resource and the operation (retrieving data). However, it lacks an explicit verb like 'get or 'retrieve', and while it distinguishes from siblings by name, it does not explicitly state what makes this tool unique.

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 other option-related tools (e.g., option_premium_analysis_em, option_risk_analysis_em). It does not mention any context, prerequisites, or alternative tools, leaving the agent to infer usage from the name and source.

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