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Agent Data Tools: Prices and DeFi

Option pricing, Black-Scholes and Greeks

options_price
Read-only

Price a European call and put with Black-Scholes-Merton and get delta, gamma, vega (per vol point), theta (per day), rho, d1, d2 and the probability of ending in the money; or give a market price and get the implied volatility. Inputs: spot, strike, expiry date or days, volatility, interest rate and dividend or funding yield in percent. Pure arithmetic, no data source. Use for crypto, stock or FX options, to price a quote or size a hedge. Example: spot=100, strike=100. Price $0.01/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

Input Schema

NameRequiredDescriptionDefault
volNoAnnual volatility in percent, e.g. 20 (default 50); not needed with price
daysNoDays to expiry (default 30), or give expiry or years
rateNoRisk-free rate in percent per year, e.g. 5 for 5% (default 0)
spotYesPrice of the underlying
typeNocall or put, for the implied volatility (default call)
priceNoA market option price: returns the implied volatility
yearsNoYears to expiry, instead of days
expiryNoExpiry date (ISO), instead of days
strikeYesStrike price
dividendNoDividend, funding or borrow yield in percent per year (default 0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior3/5

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

Annotations already carry readOnlyHint=true and destructiveHint=false, and the description reinforces that with 'Reads or computes only and changes nothing.' The genuinely additive disclosure is the billing model - paid per call via x402 USDC, first 25 free, failed calls free - which explains why idempotentHint is false and warns that repeats are not free. It does not cover failure modes or output shape beyond the unit conventions, so it adds real but not exhaustive context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded: capability and outputs come first, then inputs, then usage, then a concrete example, then the payment note. Sentences are dense and each carries information, though the payment and free-tier detail slightly bloats an otherwise tight definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the burden of describing return values and does so precisely, including Greek units (vega per vol point, theta per day) which would otherwise be ambiguous. For a 10-parameter, two-mode arithmetic tool it covers inputs, outputs, usage and cost with nothing an agent needs missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents every parameter including defaults, the 'instead of days' alternatives and percent units. The description's parameter sentence ('spot, strike, expiry date or days, volatility, interest rate and dividend or funding yield in percent') largely restates that. The only marginal value is stressing percent-based units and the three-way expiry input, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource - 'Price a European call and put with Black-Scholes-Merton' - and enumerates the exact outputs (delta, gamma, vega, theta, rho, d1, d2, ITM probability), plus the inverse mode returning implied volatility from a market price. No sibling tool in the list prices options, so the differentiation is implicit but unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly scopes use: 'Use for crypto, stock or FX options, to price a quote or size a hedge,' which tells the agent the asset classes and the two intents. It also signals the alternative mode ('or give a market price and get the implied volatility') and that no external data source is needed. It stops short of naming when NOT to use it or a sibling alternative, keeping it at 4.

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

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