quant_detect_regime

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

The description adds behavioral context beyond the annotations by specifying the threshold logic, return value structure (dict with ticker, hurst, regime), and error handling for missing data. This complements the readOnlyHint and idempotentHint annotations.

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 concise and well-structured: a one-line summary, threshold logic, then args and returns. Every sentence adds value without 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?

Given the tool's low complexity (one parameter, clear annotations, and an existing output schema), the description sufficiently covers inputs, classification logic, output format, and error conditions. No additional details are necessary for correct 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?

The input schema already provides good descriptions for the ticker and response_format fields. The description only briefly mentions 'Args: params (TickerInput): ticker, response_format,' adding minimal value beyond the schema. With schema coverage effectively high, a baseline score of 3 is appropriate.

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 purpose: classify a ticker's regime from its daily Hurst exponent. It provides specific thresholds and regime labels, distinguishing it from sibling tools like quant_analyze_setup or quant_compute_indicators.

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 explains the classification logic and the conditions for each regime (trending, mean-reverting, random walk), providing clear context. However, it does not explicitly state when not to use this tool or suggest 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.