startup-valuation

Comparable Multiples

valuation_comparables

Read-onlyIdempotent

Calculate P/E, P/S, EV/EBITDA, or EV/Revenue multiples from public comparables, plus a regression-adjusted multiple, to benchmark startup valuation when public comparables exist.

Instructions

Market multiples from comparables: P/E, P/S, EV/EBITDA, EV/Revenue, and a regression-adjusted multiple. Method selects the ratio. Use when public comparables exist; for pre-revenue or private startups use valuation_core. Parameters apply per method: pe_ratio needs market_cap + net_income; ps_ratio needs market_cap + revenue; ev_ebitda needs enterprise_value + ebitda; ev_revenue needs enterprise_value + revenue; regression_multiple needs intercept + growth_rate + growth_coefficient (plus optional maturity/stage/geography terms). 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
`stage`	No	Company stage indicator.
`ebitda`	No	EBITDA, currency units.
`method`	Yes	Formula to apply. Options: pe_ratio = P/E = market cap / net income.; ps_ratio = P/S = market cap / revenue.; ev_ebitda = EV/EBITDA = enterprise value / EBITDA.; ev_revenue = EV/Revenue = enterprise value / revenue.; regression_multiple = Multiple = β0 + β1·g + β2·M + β3·S + β4·G.
`revenue`	No	Revenue for the period, currency units.
`geography`	No	Geography indicator.
`intercept`	No	Regression intercept β0 (base multiple).
`market_cap`	No	Market capitalisation, currency units.
`net_income`	No	Net income (earnings), currency units.
`growth_rate`	No	Revenue growth rate as a decimal (0.40 = 40%).
`market_maturity`	No	Market maturity indicator.
`enterprise_value`	No	Enterprise value (market cap + net debt), currency units.
`stage_coefficient`	No	Regression slope on stage.
`growth_coefficient`	No	Regression slope on growth (multiple points per unit growth).
`maturity_coefficient`	No	Regression slope on market maturity.
`geography_coefficient`	No	Regression slope on geography.

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

A5/5.0

Behavior5/5

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

Annotations already establish read-only, idempotent, non-destructive, and closed-world behavior, but the description adds meaningful operational context: pure arithmetic with no I/O or external calls, no auth/rate limits, 2-decimal rounding, and error behavior for unknown methods or missing required parameters.

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

Conciseness5/5

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

Despite being fairly long, the description is dense and front-loaded: purpose first, then usage, then parameter rules, then return/behavior details. Every sentence adds actionable information for a 15-parameter, method-branching calculation tool.

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 complex valuation tool with many optional parameters, an output schema, and rich annotations, the description covers the remaining gaps: method selection, alternative tooling, parameter requirements, error cases, determinism, and rounding. Nothing an agent needs to select and call it correctly is missing.

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

Parameters5/5

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 each field, but the description adds critical method-to-parameter mapping (pe_ratio needs market_cap + net_income, etc.) and states that only method is required while other parameters are method-dependent and should be omitted when unused.

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 resource and the set of computed multiples (P/E, P/S, EV/EBITDA, EV/Revenue, regression multiple), making the tool's output unambiguous. It also distinguishes itself from a sibling by directing pre-revenue/private-startup cases to valuation_core.

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 gives explicit when-to-use guidance ('Use when public comparables exist') and a clear alternative for the excluded case ('for pre-revenue or private startups use valuation_core'). The method-dependent parameter guidance further tells the agent how to invoke the tool correctly.

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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