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

Annotations only cover the read-only/non-destructive safety profile, and the description adds substantial behavioral context: the numerical method (Newton-Raphson with bisection fallback), the failure modes it handles (flat vega, deep ITM/OTM, short-dated), and the explicit refusal behavior with converged:false + error rather than a garbage result.

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?

Front-loads the core purpose, then layers failure handling and usage routing in two compact follow-ups. Every clause carries information: algorithm choice, edge-case handling, and return shape.

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?

With no output schema, the description enumerates the return fields (impliedVolatilityPct, iterations, method, converged, priceAtSolution), and it covers failure semantics, so an agent has everything needed to call and interpret the tool.

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 already 83%, so the schema documents the inputs well. The description only references spot/strike/rate in passing for the no-arbitrage bounds and adds no syntax, units, or format detail beyond the schema, so baseline 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?

States a precise verb+resource: solving for the volatility that makes Black-Scholes reproduce an observed price. It clearly differentiates from the sibling run_black_scholes by inverting the direction of the computation ('not the reverse').

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 an explicit trigger ('what IV does this option price imply?' or a market price with volatility wanted) and an exclusion via 'not the reverse', which routes away from the forward-pricing sibling. It stops short of naming the alternative tool explicitly.

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