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Glama

valuation-api

calculate_moic

Read-onlyIdempotent

Calculate the Multiple on Invested Capital (MOIC): total distributions divided by total invested, with no discounting and no time value. WHEN TO USE: for a quick money-multiple answer from a cash-flow schedule when you do not need a discount rate or annualised return. WHEN NOT TO USE: when time value of money matters (use calculate_irr for annualised return, or calculate_npv for discounted value). BEHAVIOUR: pure deterministic calculation — no side effects, no network or storage access; idempotent and non-destructive. MOIC is computed as sum of positive cash flows divided by sum of absolute negative cash flows; returns 0 if there is no invested capital. RETURNS: JSON object { moic: number rounded to 2dp (e.g. 2.5 = 2.5x), cash_flows }. PARAMETERS: cash_flows (ordered number array starting at time 0; negatives are investments, positives are distributions), e.g. [-100000, 0, 0, 0, 0, 250000].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cash_flowsYesOrdered cash flows starting at time 0. Negative = invested capital, positive = distributions. Example: [-100000, 0, 0, 0, 0, 250000].

TDQS

A4.7/5.0
Behavior5/5

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

The description goes beyond annotations by stating the calculation is pure deterministic, has no side effects/network/storage access, and returns 0 when there is no invested capital. It also clarifies the exact MOIC computation rule, adding behavioral detail not present in annotations alone.

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 labeled sections and front-loads the core definition and formula. Each sentence adds useful context, and the labels make it easy to scan for purpose, behavior, return shape, and parameters.

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?

Despite having no output schema, the description documents the return JSON shape, rounding behavior, and an example output. Combined with parameter details, usage boundaries, and edge-case behavior, it provides everything an agent needs to call this tool correctly.

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?

The schema already fully describes cash_flows with ordering, sign convention, and an example, so the description adds little new parameter-level meaning. It restates the same semantics and formula, which is helpful but not a substantive addition beyond 100% schema coverage.

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 clearly identifies the tool as calculating MOIC with an explicit formula (distributions / invested) and states it has no discounting or time value. This distinguishes it from sibling tools like calculate_irr and calculate_npv even before reading their schemas.

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?

The description provides explicit 'WHEN TO USE' and 'WHEN NOT TO USE' guidance, including named alternatives (calculate_irr for annualized return, calculate_npv for discounted value). An agent can decide between sibling tools with no ambiguity.

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

A4.3/5.0
Disambiguation5/5

Every tool targets a distinct financial metric or formula, and the WHEN TO USE / WHEN NOT TO USE guidance clearly separates closely related concepts like DSO vs. receivables turnover, current vs. quick vs. cash ratio, and DPI/RVPI/TVPI. Even the overlapping investment-return tools (NPV, IRR, MOIC, payback) are explicitly differentiated.

Naming Consistency4/5

The overwhelming majority of tools follow a clean calculate_<metric> snake_case pattern, making the set highly predictable. The single exception is irr_sensitivity, which breaks the calculate_ prefix convention but is still readable and not chaotic.

Tool Count2/5

At 52 tools, this far exceeds the 25+ threshold where a tool set becomes too heavy for its scope. Although each tool is a distinct pure calculation, the sheer breadth creates a large navigation and selection burden for agents.

Completeness4/5

The server covers an unusually broad range of valuation workflows: time value of money, DCF/WACC/cost of capital, relative valuation multiples, profitability/liquidity/efficiency ratios, and private equity fund metrics. Minor gaps exist, such as no dedicated free cash flow, net debt, or EBITDA margin calculators, but these are workable around.

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