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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description adds substantive behavioral caveats: data availability from November 2006, the Vix type only from October 2019, and pre-2013 data being sampled roughly weekly rather than daily. It also clarifies that volumes are contract counts, which is valuable for correct interpretation of results.

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 compact: three sentences each earning their place. The first states the purpose, the second provides sentiment interpretation, and the third gives data-availability caveats. It is front-loaded and free of 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 data-retrieval tool with moderate complexity and no output schema, the description covers the essential context: what data is returned, how to interpret it, units, and historical availability. It does not describe the exact response record format, but the combination of sentiment thresholds, type list, and data-range caveats is sufficient for correct invocation and basic interpretation.

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 documents all four parameters with 100% coverage, so the description does not need to repeat parameter syntax. It adds interpretive thresholds and historical context, but does not introduce new parameter-specific semantics beyond what the schema provides. This aligns with the baseline of 3 for high schema coverage.

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 opens with a specific verb+resource pair ('Get CBOE put/call ratio data') and immediately frames the purpose as showing market sentiment, making it easy to distinguish from the many sibling Get* tools. It enumerates the available data types, further clarifying the exact scope of the tool.

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 gives clear context for when to use this tool: when CBOE put/call ratio data is needed, with specific available types and historical coverage. It does not explicitly name alternatives or exclusions, but the 'showing market sentiment' framing and the type list provide sufficient orientation among the large set of sibling tools.

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