startup-valuation

Pre-Revenue Core Methods

valuation_core

Read-onlyIdempotent

Compute early-stage startup valuations via pre-revenue methods like Scorecard, Berkus, and VC Method. Provide the required parameters to receive a calculated value with assumptions and steps.

Instructions

The textbook's pre-revenue methods: Scorecard, Berkus, Risk-Factor Summation, VC Method (post- and pre-money), and exit terminal value. Use these first for early-stage startups. Method selects the formula, and each method names its own parameters: scorecard needs average_valuation + weights + scores; berkus takes five factor awards; risk_factor needs base_valuation + risk_ratings; vc_post_money needs terminal_value + target_return; vc_pre_money needs post_money + investment; terminal_value needs projected_revenue + multiple; triangulated needs the scorecard inputs plus terminal_value/target_return/investment. Routing: for SAFEs, tokens, ESG, network effects, or data-moat methods use valuation_emerging; for options or bull/base/bear scenario tables use valuation_advanced; for public-comparable multiples use valuation_comparables. 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

Name	Required	Description
`method`	Yes	Formula to apply. Options: scorecard = V = V_avg · Σ(wᵢ·sᵢ) across 7 factors.; berkus = V = Σ factor awards, each capped at $500K.; risk_factor = V = V_base + Σ(rᵢ·$250K) over 12 risks.; vc_post_money = Post = Terminal / target ROI.; vc_pre_money = Pre = Post - Investment.; terminal_value = Terminal = projected revenue × multiple.; triangulated = Runs Scorecard and the VC Method together and returns their mean.
`scores`	No	Factor multipliers aligned with weights (1.0 = average, >1 above average).
`weights`	No	Portfolio or factor weights, each in [0,1] and summing to 1 (same order as the paired value list).
`multiple`	No	Exit or market multiple applied to the metric.
`prototype`	No	Berkus award for prototype / technology, 0 to 500,000.
`investment`	No	Amount invested, currency units.
`post_money`	No	Post-money valuation, currency units.
`sound_idea`	No	Berkus award for soundness of the idea, 0 to 500,000 (USD).
`quality_team`	No	Berkus award for management team, 0 to 500,000.
`risk_ratings`	No	12 risk factor ratings in [-2,2] (very low to very high); each unit shifts value ±250,000.
`target_return`	No	VC target return multiple (e.g. 10 for a 10x target).
`base_valuation`	No	Pre-adjustment baseline valuation, currency units.
`terminal_value`	No	Expected exit / terminal value, currency units.
`product_rollout`	No	Berkus award for product rollout / sales, 0 to 500,000.
`average_valuation`	No	Average pre-revenue valuation for the sector, currency units.
`projected_revenue`	No	Projected revenue at exit, currency units.
`strategic_relationships`	No	Berkus award for strategic relationships, 0 to 500,000.

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').

Schema Changelog

Changes observed during successful MCP inspections.

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 read-only annotations, it discloses that the tool is pure arithmetic with no I/O, external calls, authentication, credentials, or rate limits. It also states that results are rounded to 2 decimals and that invalid method or missing required method parameters return an error rather than a value.

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?

The description is long but front-loaded and dense with routing, method-parameter mapping, return details, and safety constraints. It earns most of its length given 17 parameters and 7 methods, though it could be structured with clearer separators for faster scanning.

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?

Given 17 parameters, seven methods, full schema coverage, and an output schema, the description is complete: it covers routing, required versus optional inputs, return shape, arithmetic behavior, error handling, and security/rate-limit context. An agent has everything needed to select and invoke the tool correctly.

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?

Although schema coverage is already 100%, the description adds meaningful method-to-parameter mapping that the schema does not: it names the exact parameters needed for scorecard, berkus, risk_factor, vc_post_money, vc_pre_money, terminal_value, and triangulated. It also explains that only method is strictly required and that other parameters should be omitted when not needed for the selected method.

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?

The description names the specific pre-revenue valuation methods covered and explicitly routes to sibling tools for other methods. An agent can distinguish this tool from valuation_emerging, valuation_advanced, and valuation_comparables without opening their schemas.

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?

It states when to use this tool first (early-stage startups) and gives explicit routing rules to alternatives for SAFEs, tokens, ESG, network effects, options, scenario tables, and public-comparable multiples. It also clarifies that only method is required and the rest are method-dependent.

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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