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parmarnaresh86

SAP Business One Order-to-Cash MCP Server

calc_eoq

Calculate optimal order quantities and expected orders per year using the Economic Order Quantity formula based on annual demand, ordering cost, and holding cost.

Instructions

Economic Order Quantity (EOQ = √(2DS / H)) for each item. D = annual demand, S = ordering cost per order, H = holding cost per unit per year (unit cost × holding rate). Returns optimal order quantities and expected orders per year.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNNoMax items to return (default 50)
holdingRateNoAnnual holding cost as fraction of unit cost (default 0.25 = 25%)
demandMonthsNoMonths of sales history for demand estimate (default 12, max 24)
orderingCostNoFixed cost per purchase order (default 50)
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the formula and the calculation outputs, but it does not explicitly state that this is a read-only analytical operation with no side effects, which matters given the many create_* and apply_* siblings.

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 compact, front-loaded with the core formula, and every sentence serves a purpose: defining the calculation, its variables, and its outputs. There is no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has only four optional parameters, all documented in the schema, and the description covers the formula and return values. It lacks an explicit statement about data sources or when to prefer this over similar tools, but for a calculation tool this is mostly complete.

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% with each parameter already described, so the baseline is 3. The description adds useful formula-level context by mapping holdingRate to H and orderingCost to S, but it does not add meaning beyond the schema for topN or demandMonths.

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 names the exact calculation ('Economic Order Quantity'), provides the formula, defines each variable, and states what it returns ('optimal order quantities and expected orders per year'). This clearly distinguishes it from related inventory tools like calc_reorder_point or predict_stockout.

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

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as calc_reorder_point or monitor_reorder_items. The formula implies inventory optimization, but no explicit context, exclusions, or sibling comparisons are provided.

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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