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storehausai

ECOUNT MCP Server

by storehausai

ecount_create_purchase

Register purchase and receiving slips in ECOUNT ERP by specifying product code, quantity, price, and supplier. Items sharing an upload serial number are combined into a single slip.

Instructions

구매 입력. 구매(입고) 전표를 ECOUNT에 등록합니다. 협력사로부터 물품을 구매하여 입고받았을 때 사용합니다. 품목코드(PROD_CD)는 필수이며, 수량/단가/금액을 입력합니다. UPLOAD_SER_NO가 같은 항목들은 하나의 구매전표로 묶입니다. [Rate Limit: 10초/1회] [Response: success(성공건수), failed(실패건수), slipNos(전표번호 배열 - YYYYMMDD-N 형식), details(상세결과 - IsSuccess, TotalError, Errors 배열)]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYes구매 품목 목록. 1~300건. UPLOAD_SER_NO가 같은 항목들은 하나의 구매전표로 묶임
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the rate limit (10초/1회), response structure (success, failed, slipNos, details), and the grouping behavior via UPLOAD_SER_NO. It does not mention idempotency or failure atomicity, but the core behavioral traits are covered.

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 compact and front-loaded with the purpose. The first two phrases '구매 입력' and '구매(입고) 전표를 ECOUNT에 등록합니다' are somewhat redundant, but the overall length is appropriate and includes rate limit and response info in brackets without bloat.

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?

For a create tool with a nested array schema and no output schema, the description covers the essential context: when to use, required field (PROD_CD), grouping key, rate limit, and response format. It does not explain prerequisites like authentication or field validation, but the schema covers parameter details.

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 already documents all parameters. The description adds only a general statement about quantity/unit price/amount and reinforces the grouping rule, which is already in the schema. It does not add significant new meaning beyond the schema.

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 states a specific verb ('등록', to register), a resource ('구매(입고) 전표', purchase/receiving slip), and a clear scenario ('협력사로부터 물품을 구매하여 입고받았을 때'). This distinguishes it from sibling create tools like ecount_create_sale or ecount_create_quotation.

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?

It explicitly says when to use it: when purchasing goods from a partner and receiving them into stock. It does not name alternative tools for exclusions, but the context is clear enough to guide selection among siblings.

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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