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Glama

Valuation API

by io.github.johnbehar1500-ux

calculate_enterprise_value

Read-onlyIdempotent

Calculate enterprise value (EV): the total value of a business to all capital providers — equity value plus net debt (total debt minus cash and equivalents). Formula: EV = Equity Value + Total Debt - Cash & Equivalents. WHEN TO USE: Use as the capital-structure-neutral measure of a company’s total value — the standard starting point for valuation multiples (EV/EBITDA, EV/Revenue) and M&A transaction values. WHEN NOT TO USE: Do NOT confuse EV with equity value (market cap) — EV is what you would pay to own the whole enterprise including its debt; use equity value for per-share figures. 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 { enterprise_value: number (currency), inputs }. PARAMETERS: equity_value (required): Equity value / market capitalisation, e.g. 5000000. Must be >= 0. total_debt (required): Total interest-bearing debt (short + long term), e.g. 2000000. Must be >= 0. cash_and_equivalents (required): Cash and cash equivalents to subtract, e.g. 500000. Must be >= 0.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
total_debtYesTotal interest-bearing debt (short + long term), e.g. 2000000. Must be >= 0.
equity_valueYesEquity value / market capitalisation, e.g. 5000000. Must be >= 0.
cash_and_equivalentsYesCash and cash equivalents to subtract, e.g. 500000. Must be >= 0.

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds meaningful behavioral context: pure deterministic calculation, no side effects, no network/storage access, identical inputs yield identical outputs, and explicit error behavior for division by zero or non-finite inputs. This goes well beyond the annotations without contradicting them.

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 well-organized with labeled sections (BEHAVIOUR, WHEN TO USE, PARAMETERS) and front-loads the formula. It is somewhat verbose, with the formula stated twice and parameter descriptions nearly duplicating the schema, but each section serves a clear purpose and the length is justified by the completeness.

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 3-parameter deterministic calculation with no output schema, the description covers everything needed: formula, input meanings with examples, constraints, return shape ({ enterprise_value, inputs }), error behavior, and use-case guidance. Nothing required to call the tool correctly 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 baseline is 3. The description adds value by embedding each parameter in the formula context, providing concrete examples (e.g., 5000000, 2000000, 500000), and restating the minimum-zero constraint in natural language. It does not introduce semantics absent from the schema, but the examples and formula linkage justify a score above baseline.

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 ('Calculate enterprise value'), provides the formula (EV = Equity Value + Total Debt - Cash & Equivalents), and explicitly distinguishes EV from equity value, which is a key confusion point. Among siblings it clearly differentiates itself as the base EV calculation rather than EV/EBITDA or EV/Revenue multiples.

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' section identifies EV as the capital-structure-neutral measure and starting point for valuation multiples and M&A values. Explicit 'WHEN NOT TO USE' section warns against confusing EV with equity value and directs agents to use equity value for per-share figures. This gives clear selection guidance relative to alternatives.

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.

Resources