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calculate_equity_multiplier

Read-onlyIdempotent

Calculate the equity multiplier: total assets divided by shareholders’ equity — a leverage measure of how many units of assets each unit of equity supports. Formula: Equity Multiplier = Total Assets / Shareholders’ Equity. WHEN TO USE: Use in DuPont analysis to quantify the financial-leverage component of return on equity, or on its own to gauge how many units of assets each unit of equity supports. WHEN NOT TO USE: Do NOT use alone — a high multiplier can mean efficient leverage or distress depending on profitability (interpret it alongside margin and turnover analysis). 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 or non-finite inputs returns an explicit error instead of a number. RETURNS: JSON object { equity_multiplier: number (e.g. 3.6 = 3.6x), inputs }. PARAMETERS: total_assets (required): Total assets, e.g. 720000. Must be > 0. shareholders_equity (required): Total shareholders’ equity, e.g. 200000. May be negative in distress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
total_assetsYesTotal assets, e.g. 720000. Must be > 0.
shareholders_equityYesTotal shareholders’ equity, e.g. 200000. May be negative in distress.

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 readOnly, non-destructive, and idempotent behavior, and the description reinforces this with concrete guarantees: no side effects, no network/storage access, deterministic outputs, and explicit division-by-zero/non-finite input error handling. This adds valuable behavioral detail 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-structured with scannable labeled sections (formula, when to use, behavior, returns, parameters), and every section earns its place. It is slightly redundant because the opening sentence restates the formula given in the FORMULA section, but this is minor and aids clarity.

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?

With no output schema present, the description appropriately specifies the return shape: a JSON object containing equity_multiplier and inputs. It also covers parameter constraints, error behavior, and interpretation context, making the tool fully understandable without additional sources.

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 the mathematical relationship between the two parameters, concrete example values, and clarifies that shareholders' equity may be negative in distress, giving agents slightly more semantic grounding than the schema alone.

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 starts with a specific verb and resource ('Calculate the equity multiplier') and defines the exact formula: total assets divided by shareholders' equity. It clearly distinguishes itself from sibling ratio calculators by specifying both the formula and its role as the leverage component in DuPont analysis.

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' and 'WHEN NOT TO USE' sections state that it belongs in DuPont analysis and should not be interpreted alone. It also names complementary analyses (margin and turnover) needed for proper interpretation, which gives an agent clear routing and contextual guidance.

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

A4.7/5.0
Disambiguation5/5

Each tool computes a distinct, named financial ratio with a unique formula; even the three liquidity ratios are carefully differentiated by strictness and explicit WHEN TO USE/NOT guidance. There is no practical risk of an agent selecting the wrong tool.

Naming Consistency5/5

All tools follow the identical calculate_<metric> pattern in snake_case, making the naming scheme highly predictable. The only minor variation is calculate_defensive_interval instead of ..._ratio, but it still fits the same verb-prefixed convention.

Tool Count5/5

Eight tools is a well-scoped set for a liquidity and leverage ratio calculator: four liquidity measures and four leverage measures, with no redundant or filler tools. The count is manageable for an agent to choose from without being over-conservative.

Completeness5/5

The tool surface covers the standard liquidity ratios (current, quick, cash, defensive interval) and the core leverage/solvency ratios (debt-to-assets, debt-to-equity, equity multiplier, interest coverage). Since each tool is a pure calculation with no stateful workflow, there are no dead-end operations or lifecycle gaps.

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