ExitValue.ai M&A Multiples

Compare industries' M&A multiples

compare_industries

Read-onlyIdempotent

Read-only. Puts 2-6 industries side by side for one metric: median multiple, middle 50% (25th-75th percentile) and deal count n per industry, using the same data, name matching and thresholds as get_valuation_multiples. Without size_bracket it compares all-deal-size medians (n>=5); with size_bracket it compares that enterprise-value bracket (n>=10). Rows below the threshold are marked INSUFFICIENT DATA rather than estimated; unmatched names and industry-group ids are flagged per row. Use it for 'which sells for more, X or Y?' questions; use get_valuation_multiples for the full breakdown of one industry.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "industries": "<industries>"
    },
    "name": "compare_industries"
  }
}

Input Schema

Name	Required	Description	Default
`metric`	No	Multiple to compare: ev_ebitda (enterprise value / EBITDA, default) or ev_revenue (enterprise value / revenue).	ev_ebitda
`industries`	Yes	2 to 6 sub-vertical ids or plain-English industry names to compare, e.g. ['dental-practice', 'veterinary-practice', 'physical therapy'].
`size_bracket`	No	Optional enterprise-value (deal size) bracket: under_5m_ev = under $5M, 5m_25m_ev = $5M-$25M, 25m_100m_ev = $25M-$100M, 100m_500m_ev = $100M-$500M, over_500m_ev = $500M and up. Omit to compare all deal sizes pooled.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 29, 2026

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, but the description adds genuine behavioral context beyond them: sample thresholds (n>=5 pooled vs n>=10 within a bracket), that rows below threshold are marked INSUFFICIENT DATA rather than estimated, and that unmatched names and industry-group ids are flagged per row. These are data-quality behaviors an agent could not infer from any structured field.

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?

Safety and output scope are front-loaded, then thresholds, then routing. Every clause carries information, though the mid-section is dense with multiple constraints packed into two long sentences, slightly reducing scannability.

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?

No output schema exists, yet the description names the returned statistics (median, 25th-75th percentile, n) and the flag values, and covers threshold behavior, name mapping, and the sibling split. Nothing an agent needs to call this correctly or interpret it 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 is 3. The description adds real meaning on top: it explains that omitting size_bracket changes the comparison population and the minimum-n threshold, which the schema only partially conveys ('omit to compare all deal sizes pooled').

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 ('puts 2-6 industries side by side for one metric') and enumerates exactly what is returned. It is immediately distinguishable from get_valuation_multiples, which it names as the single-industry alternative.

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 routing: 'Use it for which sells for more, X or Y? questions; use get_valuation_multiples for the full breakdown of one industry.' The when-to-use and the alternative are both stated without inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ExitValue.ai M&A Multiples tools Inspect

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