startup-valuation

Options & Scenario Analysis

valuation_advanced

Read-onlyIdempotent

Compute Black-Scholes call values, binomial-tree option values, or explicit bull/base/bear scenario expected values. Select a method and supply only its required inputs.

Instructions

Advanced techniques: Black-Scholes call value, binomial-tree option value, and scenario analysis. Method selects the technique. For a quick expected value over arbitrary outcome lists, prefer valuation_probability with method 'probability_weighted'; scenario_analysis here is for explicit named bull/base/bear scenario tables. Parameters apply per method: black_scholes and binomial need underlying + strike + risk_free_rate + volatility + time_to_maturity (binomial adds steps); scenario_analysis needs scenarios. Not for plain discounted cash flow — for that use valuation_time_value. Only method is required; all other parameters are method-dependent, so supply those the selected method names and omit the rest (defaults apply where defined). Rate and decimal inputs are fractions (0.10 = 10%); probability and weight lists are in [0,1] and sum to 1. Returns value, method, inputs, assumptions, chapter, formula_number and calculation steps; pure arithmetic — no I/O and no external calls — rounded to 2 decimals, with no auth or rate limits. An unknown method, or a missing method-required parameter, returns an error instead of a value.

Input Schema

TableJSON Schema

Name	Required	Description
`steps`	No	Binomial tree time steps (integer ≥ 1; higher = more accurate).
`method`	Yes	Formula to apply. Options: black_scholes = C = N(d₁)S - N(d₂)Ke^(-rT).; binomial = Cox-Ross-Rubinstein binomial option value.; scenario_analysis = E[V] = Σ pᵢ·Vᵢ over named scenarios.
`strike`	No	Strike / exercise price K, currency units.
`scenarios`	No	Scenario objects: {name: str, probability: 0-1, value: currency}; probabilities should sum to 1.
`underlying`	No	Underlying asset value S, currency units.
`volatility`	No	Annualised volatility σ as a decimal (0.80 = 80%).
`risk_free_rate`	No	Risk-free rate as a decimal (e.g. 0.04 for 4%).
`time_to_maturity`	No	Time to expiry in years T, must be ≥ 0.

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No	Error message when the call fails.
`steps`	No	Intermediate steps for traceability.
`value`	Yes	Computed valuation or metric.
`inputs`	No	Echo of the normalised inputs used.
`method`	No	Formula / method name that produced the result.
`chapter`	No	Source textbook chapter.
`assumptions`	No	Modelling assumptions applied.
`formula_number`	No	Source textbook formula number (e.g. '3.1').
`defaults_applied`	No	Optional parameters that were not supplied, so their documented defaults were used.

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv2.1.1Oct 2, 2026

changedInput schema / properties / steps / description

Previous value: -"Binomial tree time steps (higher = more accurate)."New value: +"Binomial tree time steps (integer ≥ 1; higher = more accurate)."

changedInput schema / properties / time_to_maturity / description

Previous value: -"Time to expiry in years T."New value: +"Time to expiry in years T, must be ≥ 0."

addedOutput schema / properties / defaults_applied

Added value: +{
+  "description": "Optional parameters that were not supplied, so their documented defaults were used.",
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}

First observedv0.1.0Sep 30, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive, closed world), the description discloses error behavior for unknown methods and missing required params, that outputs are rounded to 2 decimals, that computation is pure arithmetic with no I/O or external calls, and that there is no auth or rate limiting.

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-loads the techniques, then routing, then method-parameter requirements, then output/behavioral notes. Dense but each sentence carries information; the only slight redundancy is restating return fields when an output schema exists.

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?

For an 8-parameter, method-dispatched tool with an output schema, the description covers method selection, per-method required inputs, units/conventions, failure modes, and side-effect profile — nothing an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is 100% so per-parameter meanings are already documented, but the description adds the method-to-parameter mapping (which fields black_scholes/binomial/scenario_analysis require), notes steps only applies to binomial, and clarifies that rate/decimal inputs are fractions in [0,1] — genuine value beyond the schema.

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 specific verbs and resources (Black-Scholes call value, binomial-tree option value, scenario analysis) and explicitly distinguishes itself from sibling tools, naming valuation_probability and valuation_time_value as the alternatives for other tasks.

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

Usage Guidelines5/5

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

Gives explicit when-to-use routing: use valuation_probability with method 'probability_weighted' for quick expected values over arbitrary outcome lists, use scenario_analysis here for named bull/base/bear tables, and use valuation_time_value for plain DCF. Each alternative names the condition that selects it.

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

Deploy Server