get_unusual_options

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

With no annotations provided, the description carries the full behavioral disclosure burden. It discloses the specific filtering logic (Volume > OI or IV > 50%) and purpose, but does not mention data source, real-time vs delayed data, or any limitations. This is adequate but leaves notable gaps.

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 a single concise sentence that packs essential information: what it scans, the exact criteria, and the purpose. Every word earns its place; zero 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 simplicity (one parameter, full schema coverage, output schema present), the description is complete enough. It explains the tool's function, how it filters, and why it exists. The output schema handles return value details, so no further description is needed.

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%, with the only parameter (symbol) already documented as 'Stock ticker (e.g. AAPL, NVDA, TSLA)'. The description does not add additional meaning about the parameter 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 uses a specific verb ('scans') and clearly identifies the resource ('unusual options activity') with explicit detection criteria and purpose. It distinguishes itself from sibling tools like get_options_chain or get_options_analytics by focusing on unusual activity rather than general option data.

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 context by stating the detection criteria and intended use ('to detect smart money positioning'), but it does not explicitly mention alternative tools or when not to use this tool. This is clear context without exclusions, matching a score of 4.

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