startup-valuation

Hardware & Unit Economics

valuation_hardware

Read-onlyIdempotent

Computes hardware and deep-tech valuations using TRL-risk adjustment, gross margin, or break-even volume to assess technology-readiness risk.

Instructions

Hardware and deep-tech valuation: TRL-risk-adjusted valuation, gross margin, and break-even volume. Method selects the metric. Use for hardware and deep tech with technology-readiness risk; for drug pipelines use valuation_biotech. Parameters apply per method: trl needs market_size + market_share + margin + multiple + trl_discount; gross_margin needs asp + variable_cost; break_even_volume needs fixed_costs + asp + variable_cost. Not for drug pipelines — for those use valuation_biotech. 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
`asp`	No	Average selling price per unit, currency units.
`margin`	No	Profit margin as a decimal.
`method`	Yes	Formula to apply. Options: trl = V = market × share × margin × multiple × (1 - TRL discount).; gross_margin = GM = (ASP - COGS) / ASP.; break_even_volume = Units = fixed costs / (ASP - variable cost).
`multiple`	No	Exit or market multiple applied to the metric.
`fixed_costs`	No	Fixed costs for the period, currency units.
`market_size`	No	Total addressable market, currency units.
`market_share`	No	Target market share as a decimal in [0,1].
`trl_discount`	No	TRL risk discount as a decimal (applied as 1 - discount).
`variable_cost`	No	Variable cost per unit, currency units.

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.

Changed2 schema fields changedv2.1.1Oct 2, 2026

changedInput schema / properties / market_share / description

Previous value: -"Target market share as a decimal."New value: +"Target market share as a decimal in [0,1]."

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

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world. The description adds that unknown methods or missing method-required parameters return an error, that inputs are fractions (0.10 = 10%), that probability/weight lists are in [0,1] summing to 1, and that it is pure arithmetic with no auth or rate limits. The return fields are listed, though an output schema exists so that is bonus rather than necessary.

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 front-loaded with purpose, then method routing, then the 'not for' exclusion, parameter guidance, and input conventions. It is information-dense and every sentence carries useful content, though the 'Not for drug pipelines — for those use valuation_biotech' clause repeats the earlier sibling exclusion, which is slightly redundant.

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 9-parameter tool with one required parameter, method-dependent inputs, an output schema, and enum-valued method, the description covers selection, per-method inputs, conventions, error behavior, and return shape. An agent has everything needed to invoke it 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?

Schema coverage is 100%, so the schema already documents each parameter type and meaning; baseline would be 3. The description adds method-to-parameter mapping (trl needs market_size + market_share + margin + multiple + trl_discount; gross_margin needs asp + variable_cost; break_even_volume needs fixed_costs + asp + variable_cost) and the fraction/list conventions, which is meaningful cross-parameter semantics the schema does not encode.

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 states specific verbs and resources — 'TRL-risk-adjusted valuation, gross margin, and break-even volume' — matching the three enum methods. It explicitly distinguishes from the sibling valuation_biotech, making it easy for an agent to select among the valuation_* family.

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?

Explicit when-to-use ('for hardware and deep tech with technology-readiness risk') and when-not ('Not for drug pipelines — for those use valuation_biotech'), naming the alternative tool twice. Method-dependent parameter requirements are also spelled out so the agent knows which inputs to supply.

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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