indicator_volatility_regime

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

No annotations are provided, and the description lacks behavioral details such as computational cost, edge cases (e.g., insufficient data), or the exact output structure. The description does not disclose traits beyond what can be inferred from the input schema.

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 (two sentences) and front-loaded, stating the core functionality first. Every sentence adds value, with no redundancy.

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?

Despite good parameter descriptions and a clear purpose, the description omits the output format (e.g., whether it returns a string label, probability, or object). Since there is no output schema, this information is critical for correct tool usage.

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 100%, so each parameter is described. The tool description mentions the use of Bollinger Band width percentile, which ties to 'bbPeriod' and 'lookback', but adds no new semantics beyond the schema. Baseline of 3 is maintained.

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 that the tool classifies volatility regimes based on Bollinger Band width percentile, listing five categories. However, it does not differentiate from the sibling 'indicator_volatility_regime_direct' or specify the output format (e.g., single string label).

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 usage for position management and strategy selection ('辅助 AI 做仓位管理和策略选择'), but provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among sibling tools.

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