efficiency

calculate_days_inventory_outstanding

Read-onlyIdempotent

Calculate days inventory outstanding (DIO): the average number of days a company holds inventory before selling it. Formula: DIO = 365 / Inventory Turnover. WHEN TO USE: Use to assess inventory efficiency and capital tied up in stock; high DIO risks obsolescence and cash drag. WHEN NOT TO USE: Do NOT apply mechanically across industries — optimal DIO differs hugely between fresh grocery and heavy machinery. 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 { days_inventory_outstanding: number of days (e.g. 60.8), inputs }. PARAMETERS: cogs (required): Cost of goods sold for the period, e.g. 600000. Must be > 0. begin_inventory (required): Inventory at period start, e.g. 90000. Must be >= 0. end_inventory (required): Inventory at period end, e.g. 110000. Must be >= 0.

Input Schema

TableJSON Schema

Name	Required	Description
`cogs`	Yes	Cost of goods sold for the period, e.g. 600000. Must be > 0.
`end_inventory`	Yes	Inventory at period end, e.g. 110000. Must be >= 0.
`begin_inventory`	Yes	Inventory at period start, e.g. 90000. Must be >= 0.

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the annotations, the description states this is a pure deterministic calculation with no side effects, no network or storage access, idempotent and non-destructive behavior, and identical outputs for identical inputs. It also discloses division-by-zero and non-finite input error behavior, adding meaningful operational detail.

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, when to use, when not to use, behavior, returns, and parameters. Every sentence earns its place, and the core purpose is front-loaded in the first sentence.

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, the description compensates by specifying the exact JSON return shape: { days_inventory_outstanding, inputs }. It also explains error behavior, parameter constraints, and provides a concrete example, making the tool fully callable by an agent.

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 coverage is 100%, so the schema already fully documents all three parameters with descriptions, examples, and constraints. The description's PARAMETERS section largely mirrors the schema and adds little new meaning beyond tying the inputs to the DIO formula, so the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'Calculate days inventory outstanding (DIO)', followed by a definition and the formula DIO = 365 / Inventory Turnover. This clearly differentiates it from sibling tools like DSO, DPO, and inventory turnover by focusing on the inventory holding period.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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 sections, noting that DIO assesses inventory efficiency and capital tied up in stock, and warning against mechanical cross-industry application. It does not name sibling alternatives such as calculate_inventory_turnover or calculate_days_sales_outstanding, which would make the routing fully explicit.

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

A4.4/5.0

Disambiguation4/5

Each tool calculates a distinct financial efficiency ratio, but some boundaries are close: the turnover/day pairs (e.g., inventory_turnover vs. days_inventory_outstanding) cover conceptually related metrics, and asset_turnover vs. fixed_asset_turnover could initially be confused. The detailed WHEN TO USE guidance does help disambiguate, so misselection risk is low but not zero.

Naming Consistency5/5

All tool names follow the exact same calculate_<metric> pattern, making the set highly predictable and easy to scan. There are no mixed conventions, position variations, or inconsistent verb forms.

Tool Count5/5

Nine tools is a well-scoped size for a financial efficiency calculation server. Each tool corresponds to a standard, distinct efficiency ratio, and none feel redundant or unnecessary.

Completeness4/5

The set covers the core efficiency ratio family comprehensively: asset, fixed asset, inventory, receivable, and payable turnover, plus their days-based counterparts and the cash conversion cycle. Minor gaps remain, such as no direct working-capital-turnover or operating-cycle calculator, but agents can assemble those from the existing outputs.

Resources

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