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BizValueDash

Indicative business value range

estimate_value_range
Read-only

Return an indicative value range for a small private business from its yearly earnings and industry, using publicly reported average sale multiples. Earnings should be seller's discretionary earnings (profit before tax plus owner pay, interest and depreciation) for owner-operated businesses, or EBITDA for larger ones. Not a formal valuation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
industryNoIndustry or sector, for example "hvac", "dental", "restaurant", "manufacturing". Optional.
annual_earningsYesYearly earnings in US dollars.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description goes beyond that by flagging the heuristic nature of the output ('indicative', 'publicly reported average sale multiples') and the important caveat 'Not a formal valuation', which manages expectations about result reliability—context annotations cannot provide.

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?

Three tightly packed sentences: purpose first, then the critical definition of the earnings input, then the disclaimer. Every sentence earns its place with no preamble.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given only 2 params, full schema coverage, no output schema and a read-only annotation, the description covers purpose, input semantics and reliability caveat. It could say more about how the range is reported (currency, spread, confidence), but the essentials for correct invocation are present.

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 baseline is 3, but the description adds meaning beyond the schema: it defines what 'annual_earnings' should represent (SDE: profit before tax plus owner pay, interest and depreciation; or EBITDA for larger firms) and that 'industry' is used to select the multiple. This disambiguates a genuinely ambiguous input field.

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 (Return) and resource (indicative value range for a small private business) plus the inputs it draws on (yearly earnings, industry, public sale multiples). An agent can immediately tell what the tool produces and how it is derived.

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

Usage Guidelines3/5

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

The description implies when to use it (valuing a small owner-operated or larger private business) but never states exclusions or names alternatives. The sibling tools are unrelated (get_page, search_guides), so there is no routing conflict, but no explicit when/when-not guidance is given either.

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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