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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds the conceptual model (options market pricing, 1σ and 2σ bands) which helps interpret results, but doesn't describe output shape, units of the result, or any assumptions. Adequate but not rich.

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?

A single efficient sentence with no waste, front-loading the core output (1σ/2σ ranges) and then the inputs. Slightly dense but well-structured.

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 3-param pure computation with a fully documented schema and read-only annotations, the description covers the essentials. However, with no output schema, it leaves the return format (e.g., dollar ranges, per-σ labels) unstated. Minimum viable for the tool's complexity.

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%: each parameter has a clear description including the iv_pct convention ('30 means 30 percent') and days as calendar days. The description restates the inputs qualitatively but adds no syntax or format detail beyond the schema. Baseline 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?

Clearly states a specific computation: 1σ/2σ price ranges from options-implied volatility over a horizon. Names the required inputs (stock price, implied volatility, days) so the purpose is precise. It does not differentiate itself from siblings like profit_calculator or probability_of_profit, though the resource is distinct enough.

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?

Gives no explicit when-to-use guidance, no alternatives, and no exclusions. With nine sibling options-analytics tools, an agent gets no routing help for choosing expected_move over probability_of_profit or profit_calculator.

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