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

Beyond the readOnlyHint annotation, the description discloses the specific calculation windows (20-day, 60-day), the exact inputs (spot log-returns, ATM IV first-differences), and the typical negative correlation behavior for equity indices. This adds meaningful methodological context.

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 two sentences, dense with useful information and no filler. Each sentence contributes distinct value: defining the metric and stating its practical applications.

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 no output schema, the description explains the metric, computation, and typical behavior, which is sufficient for a read-only correlation retrieval tool. It does not describe return format, but the core functionality and use are well covered.

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 coverage is 100%, so both apiKey and symbol are already documented. The description does not add additional parameter-level semantics beyond what the schema provides, so the baseline score of 3 applies.

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 precisely defines the computation: 20-day and 60-day Pearson correlation between spot log-returns and ATM IV first-differences. It clearly identifies the metric and resource, distinguishing this from other volatility tools in the sibling list.

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?

Provides explicit use cases: assessing leverage effect strength, calibrating vanna/vol-of-vol hedges, and classifying correlation regime. While no alternatives are named, the intended contexts are clear and actionable.

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