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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so the safety profile is covered. The description goes well beyond that: it discloses the solver algorithm, the no-arbitrage bound pre-check, the refusal behavior on impossible prices (converged=false plus error rather than a garbage number), and the meaning of identifiable=false. Only minor gaps remain, such as performance or iteration limits.

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-loaded with the core purpose in the first clause, then edge cases, exclusions, and return values in a logical order with zero filler sentences. It is dense and semicolon-heavy as a single block, which slightly hurts scannability, but every sentence carries information.

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?

There is no output schema and no annotations covering return values, so the description carries that burden and does so fully: it names returned fields (impliedVolatilityPct, iterations, method, converged, identifiable, warning, priceAtSolution) and explains the semantics of the failure and warning states. For a six-parameter numerical solver, nothing an agent needs in order to call and interpret it is missing.

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%, so per-dimension baseline is 3, and the description adds real constraints not present in the schema: spot, strike, daysToExpiry and targetPriceUsd must be above zero, riskFreeRatePct is bounded 0 to 100, and the search range is 0.01 to 1000 volatility points. It does not restate units and defaults that the schema already carries, which is correct.

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: solves for the volatility that makes Black-Scholes reproduce an observed option price, including the numerical approach (Newton-Raphson with bisection fallback). It also implicitly separates itself from the sibling workflow.run_black_scholes by saying it is used when the user gives a market price and wants volatility "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?

Explicitly names the triggering user question ("what IV does this option price imply?") and the alternative direction of computation it is not for. It also enumerates exclusions (American exercise, dividends, volatility smile, bid-ask spreads, coin-settled prices) so an agent knows when to route elsewhere or pre-convert inputs.

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