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Valuation API

calculate_ev_to_ebitda

Read-onlyIdempotent

Calculate the EV/EBITDA multiple: enterprise value divided by EBITDA — the most widely used valuation multiple for comparing companies independent of capital structure, tax and depreciation policy. Formula: EV/EBITDA = Enterprise Value / EBITDA. WHEN TO USE: Use for relative valuation of cash-generative businesses against peer multiples or transaction comps; a lower multiple may indicate relative undervaluation (or justified risk). WHEN NOT TO USE: Do NOT use when EBITDA is negative or near zero, or for early-stage companies with no meaningful EBITDA — the multiple is meaningless there (use EV/Revenue). BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive; identical inputs always produce identical outputs. Division by zero, non-finite inputs, or mathematically undefined combinations return an explicit error instead of a number. RETURNS: JSON object { ev_to_ebitda: number (e.g. 8.5 = 8.5x), inputs }. PARAMETERS: enterprise_value (required): Enterprise value in currency units, e.g. 10000000. Must be > 0. ebitda (required): Earnings before interest, tax, depreciation and amortisation, e.g. 1200000. Must be > 0 for a meaningful multiple.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ebitdaYesEarnings before interest, tax, depreciation and amortisation, e.g. 1200000. Must be > 0 for a meaningful multiple.
enterprise_valueYesEnterprise value in currency units, e.g. 10000000. Must be > 0.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses behavior well beyond the annotations: pure deterministic calculation, no side effects, idempotent, non-destructive, and explicit error behavior for division by zero or non-finite inputs. This adds meaningful context on top of readOnlyHint and idempotentHint.

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?

The description is well structured with clear sections: definition, formula, use guidance, behavior, returns, and parameters. It is detailed but every section earns its place, and the core definition is front-loaded.

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 simple two-parameter deterministic calculation with no output schema, the description is complete: it defines the formula, states valid input conditions, describes error behavior, and specifies the return shape. Nothing needed to invoke the tool correctly is missing.

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

Parameters3/5

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 both parameters with examples and constraints. The description restates the parameter meaning but does not add significant new semantics beyond the formula and the restriction that values must be positive for a meaningful multiple.

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: calculates EV/EBITDA, with the formula explicitly given. It also distinguishes the multiple from EV/Revenue, which is a sibling tool, making it clear what this one is for versus alternatives.

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?

Provides explicit WHEN TO USE and WHEN NOT TO USE sections, including the condition of negative or near-zero EBITDA and a direct pointer to EV/Revenue as the alternative. This fully routes the agent to the correct tool for the right situation.

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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TDQS

A4.6/5.0
Disambiguation4/5

Most tools map cleanly to distinct valuation concepts (CAPM, WACC, DCF, multiples, NPV/IRR/MOIC, beta adjustment), so an agent can generally select correctly. The main ambiguity is that calculate_irr already includes MOIC and an IRR sensitivity table, making irr_sensitivity and calculate_moic partially overlapping in purpose despite their clarifications.

Naming Consistency4/5

The overwhelming pattern is calculate_<metric>, with clear snake_case and a consistent prefix throughout. The one outlier is irr_sensitivity, which drops the calculate_ prefix and breaks the established verb_noun convention.

Tool Count5/5

Twelve tools is a well-scoped size for a valuation calculation API, covering cost of capital, DCF, multiples, and return metrics without bloat. Each tool represents a meaningful standalone calculation an agent would need.

Completeness4/5

The core valuation workflow is well covered: cost of equity, WACC, DCF, enterprise value, multiples, and investment return metrics are all present. The notable gap is the reverse of calculate_enterprise_value—deriving equity value from enterprise value—and there is no standalone terminal value calculator, though both are workable gaps.