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efficiency

calculate_receivables_turnover

Read-onlyIdempotent

Calculate receivables turnover: net credit sales divided by average accounts receivable — how efficiently a company collects money owed by customers. Formula: Receivables Turnover = Net Credit Sales / Average Accounts Receivable. WHEN TO USE: Use to assess collection efficiency and customer credit quality; a falling ratio signals slower collections or looser credit terms. WHEN NOT TO USE: Do NOT use total revenue if a large share of sales is cash (use credit sales only), and pair with days sales outstanding for intuition. 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 { receivables_turnover: number (e.g. 8.0 = 8.0x per year), inputs }. PARAMETERS: net_credit_sales (required): Net credit sales for the period, e.g. 800000. Must be >= 0. begin_receivables (required): Accounts receivable at period start, e.g. 95000. Must be >= 0. end_receivables (required): Accounts receivable at period end, e.g. 105000. Must be >= 0.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_receivablesYesAccounts receivable at period end, e.g. 105000. Must be >= 0.
net_credit_salesYesNet credit sales for the period, e.g. 800000. Must be >= 0.
begin_receivablesYesAccounts receivable at period start, e.g. 95000. Must be >= 0.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already carry readOnlyHint=true, idempotentHint=true, destructiveHint=false; the description adds genuinely new behavioral context beyond them: no side effects/network/storage access and, importantly, that division by zero or non-finite inputs returns an explicit error rather than a number. Some content restates annotations (idempotent, non-destructive), but the error-behavior disclosure is valuable for correct invocation. No contradiction.

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?

Well-structured with labeled sections (WHEN TO USE, WHEN NOT TO USE, BEHAVIOUR, RETURNS, PARAMETERS) and front-loaded purpose sentence. However, the PARAMETERS section duplicates schema descriptions and the BEHAVIOUR section repeats annotation hints, adding mild redundancy to an otherwise efficient layout.

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 no output schema, the description explicitly documents the return shape ({ receivables_turnover: number, inputs }), provides the formula, usage boundaries, edge-case behavior, and complete parameter semantics. For a 3-parameter deterministic calculation tool, nothing an agent needs to invoke it 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 fully documents all three parameters; the PARAMETERS section largely mirrors the schema (same examples, same constraints). The formula body adds relational meaning (numerator vs. denominator, average = begin/end), but the per-parameter text adds no value beyond the schema, so baseline 3 applies.

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 receivables turnover'), gives the operational definition (net credit sales divided by average accounts receivable), and provides the explicit formula. This clearly differentiates it from siblings like days_sales_outstanding (which it names as the paired metric) and inventory/payables/asset turnover variants.

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?

Has explicit WHEN TO USE ('assess collection efficiency and customer credit quality') and WHEN NOT TO USE ('Do NOT use total revenue if a large share of sales is cash') sections. It also names the alternative sibling, days sales outstanding, telling the agent to pair with it for intuition — clear routing context with exclusions.

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.

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