article_rlab_rv

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

While annotations already declare readOnly, idempotent, and non-destructive behavior, the description introduces ambiguity by specifying ':return: pandas.DataFrame' but showing a sample output that is clearly a pandas Series (with 'Name: RV, Length: 5810, dtype: float64'). It also mentions multiple RV estimates (5-min and 15-min) without clarifying what the actual output structure is, creating confusion about the return format.

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 verbose, containing a large block of website copy including references, methodology details, and data cleaning information that is irrelevant for an agent invoking the tool. It is not front-loaded with a crisp summary, and the repeated sections make it difficult to parse quickly. Only the param/return snippet and the objective sentence are useful.

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?

With only one optional parameter and no output schema, the description should clearly define the return value and parameter constraints. It fails to do so—the return type is ambiguous (DataFrame vs Series), the symbol format is undefined, and the data coverage limitations (e.g., US equities after 2007) are not explicitly stated. The sample output helps but is inconsistent with the declared return type.

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 one parameter 'symbol' with no description (0% coverage). The description only says ':param symbol: str 股票代码' (stock code), which adds minimal meaning. It does not explain the expected format (e.g., US ticker vs. numeric code), valid symbols, or how the default '39693' is used, leaving the agent to guess what value to supply.

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 provides 'up-to-date daily annualized realized volatilities for individual stocks, ETFs, and future contracts' from the Risk Lab website, which is a specific resource. The title and sample output reinforce this, but it lacks an explicit comparison to sibling RV tools (e.g., article_oman_rv), so it does not fully distinguish from alternatives.

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?

No explicit guidance is given on when to use this tool versus other RV tools or when not to use it. The description implies it is for realized volatility data, but does not state any context, exclusions, or alternatives, leaving the agent to infer usage from the data source and methodology.

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