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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds behavioral context by explaining the data used (daily high/low/open/close) and the statistical efficiency advantage, which goes beyond the structured fields. No contradictions with 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?

Three sentences, front-loaded with the core function, followed by methodology and use cases. Every sentence adds value; no filler or 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?

For a simple read-only tool with two parameters and no output schema, the description is remarkably complete. It specifies the windows, the estimator types, the data inputs, and the intended applications. No significant gaps remain.

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?

With 100% schema description coverage, the parameters (apiKey, symbol) are already well-documented. The description adds no parameter-specific syntax or format details, but it does provide context about the underlying data used, which indirectly informs how symbol is used. This meets the baseline but does not exceed it.

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 states a specific verb ('Get'), specific resource ('realized volatility estimators'), and details the exact estimator types and windows. It clearly distinguishes itself from sibling tools like get_volatility or get_historical_volatility by emphasizing 'range-based' and listing the specific estimators.

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 clear use cases: 'measure realized vol robustly, compare estimators, or feed a vol-risk-premium calc.' It does not explicitly exclude alternative tools, but the context is sufficient for an agent to infer when this tool is appropriate.

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