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simonplmak-cloud

startup-valuation

by simonplmak-cloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Stakeholder & Equity Allocation

valuation_stakeholder
Read-onlyIdempotent

Split a known company valuation across stakeholders and equity classes using dilution, OPM, PWERM, liquidation, synergy, option, vesting, and loan models. Supply the method and its required inputs.

Instructions

Allocate value across stakeholders and equity classes: single-round dilution, OPM common stock, PWERM, liquidation value, M&A synergy, employee-option values, vesting adjustment, cash-vs-equity break-even, and asset-based loan capacity. Method selects the model. Use only after the company-level value is known (from valuation_core, valuation_saas, or valuation_comparables) to split that value across the cap table; for the company value itself do not use this tool. Parameters apply per method: dilution needs ownership_before + investment + post_money; opm needs enterprise_value + liquidation_pref + time_to_exit + volatility; pwerm and employee_option need scenarios; liquidation needs assets + recovery_rates; risk_adjusted_synergy needs revenue_synergies + cost_synergies; vesting_adjusted needs total_value + vested_fraction; max_asset_loan takes collateral values. Only method is required; other parameters are method-dependent, so supply those named for the selected method and omit the rest (documented defaults apply where defined). Returns an object with value, method, inputs, assumptions, chapter, formula_number and calculation steps. Pure arithmetic: no I/O and no external calls, and numeric results are returned rounded to 2 decimals. No authentication, credentials, or rate limits apply. Supplying an unknown method, or leaving unset a parameter that the chosen method requires, returns an error instead of a value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cashNoCash and equivalents, currency units.
yearsNoForecast horizon in years.
assetsNoMap of asset name to book value, e.g. {"cash": 500000}.
methodYesFormula to apply. Options: dilution = Ownership = before × (1 - investment / post-money).; opm = Option-pricing allocation of equity value to common shares.; pwerm = Probability-weighted expected return method across exit scenarios.; liquidation = V = Σ(asset × recovery rate).; risk_adjusted_synergy = Probability-weighted, discounted M&A revenue + cost synergies.; intrinsic_option = Intrinsic value = max(0, FMV - strike) × shares.; employee_option = Probability-weighted employee option value across scenarios.; vesting_adjusted = Option value adjusted for vesting schedule and retention probability.; cash_equity_breakeven = Break-even comparing salary reduction against discounted equity.; max_asset_loan = Borrowing capacity from asset collateral values.
sharesNoNumber of option shares.
tax_rateNoEffective tax rate as a decimal.
equipmentNoEquipment, currency units.
inventoryNoInventory, currency units.
prob_costNoProbability of realising cost synergies, 0-1.
scenariosNoScenario objects: {name: str, probability: 0-1, value: currency}; probabilities should sum to 1.
investmentNoAmount invested, currency units.
post_moneyNoPost-money valuation, currency units.
volatilityNoAnnualised volatility σ as a decimal (0.80 = 80%).
real_estateNoReal estate, currency units.
total_valueNoTotal grant value, currency units.
equity_valueNoValue of equity offered, currency units.
prob_revenueNoProbability of realising revenue synergies, 0-1.
strike_priceNoOption strike price, currency units.
time_to_exitNoExpected time to exit / liquidity in years.
discount_rateNoDiscount rate as a decimal (0.12 = 12%).
cost_synergiesNoCost synergy value, currency units.
recovery_ratesNoMap of asset name to recovery rate in [0,1], matching assets.
retention_probNoProbability the holder stays, 0-1.
vested_fractionNoFraction vested in [0,1].
years_remainingNoYears of vesting remaining.
annual_vest_rateNoAnnual vesting rate as a decimal.
enterprise_valueNoEnterprise value (market cap + net debt), currency units.
liquidation_prefNoLiquidation preference amount, currency units.
ownership_beforeNoFounder ownership before the round as a decimal (0.60 = 60%).
salary_reductionNoAnnual salary foregone for equity, currency units.
fair_market_valueNoCurrent fair market value per share, currency units.
revenue_synergiesNoRevenue synergy value, currency units.
accounts_receivableNoAccounts receivable, currency units.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoError message when the call fails.
stepsNoIntermediate steps for traceability.
valueYesComputed valuation or metric.
inputsNoEcho of the normalised inputs used.
methodNoFormula / method name that produced the result.
chapterNoSource textbook chapter.
assumptionsNoModelling assumptions applied.
formula_numberNoSource textbook formula number (e.g. '3.1').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, closed-world, non-destructive, but the description goes further: pure arithmetic with no I/O or external calls, results rounded to 2 decimals, no auth/rate limits, and error behavior for unknown methods or missing method-required parameters. These are traits the annotations do not carry.

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 with purpose and precondition, and the per-method parameter list is compressed into terse phrases. It is long, but the length is largely earned by ten distinct methods and 33 parameters; a small amount of repetition around required-vs-optional could be trimmed.

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 a multi-model calculator with an output schema present, the description covers the precondition, the method-to-parameter contract, the error surface, and numeric formatting. 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 the baseline would be 3, but the description adds genuinely new semantics by mapping each method to the specific parameters it requires (e.g. dilution needs ownership_before + investment + post_money), information the flat 33-parameter schema cannot express. It also explains that only 'method' is required and other params are method-dependent.

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 ('Allocate value across stakeholders and equity classes') and enumerates the ten allocation models it implements. It also names the sibling tools it must follow (valuation_core, valuation_saas, valuation_comparables), so an agent can place it precisely in the toolchain.

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 an explicit precondition ('Use only after the company-level value is known') and an explicit exclusion ('for the company value itself do not use this tool'), with the alternatives named. This is a textbook when/when-not statement.

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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