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WaHaiLong

Kingdee MCP Server

by WaHaiLong

kingdee_get_bill_template

Read-onlyIdempotent

Retrieves validated model skeleton templates for common Kingdee bills, including correct field names, required fields, and entry requirements so AI can replace placeholders with business data before validation.

Instructions

获取常用单据的「已验证 model 骨架」模板(销售报价单/销售订单/采购订单等)。

返回该表单的正确字段名、必填项、分录必填字段组成的 model 示例,AI 只需替换占位符填业务数据, 跳过字段摸索。占位符形如 <客户编码>。保存前建议再用 kingdee_validate_bill 校验。

支持的 form_id:SAL_Quotation / SAL_SaleOrder / PUR_PurchaseOrder(其它表单返回提示)。

Input Schema

NameRequiredDescriptionDefault
form_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.4

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so safety is covered. The description adds real behavioral value beyond that: the output is a pre-verified static skeleton, placeholders use the <...> convention, and unsupported form_ids yield a prompt rather than an error. It does not describe caching or freshness of the template, which is the only notable gap.

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?

Purpose and return content are front-loaded, followed by the usage tactic and the supported-value list. Four short lines with almost no waste; the only slight redundancy is repeating the placeholder concept after already describing the sample model.

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?

With an output schema present, return shape needs no full explanation, and the description still characterizes it well. For a single required parameter with rich annotations, the definition covers purpose, allowed values, and next-step validation; only template staleness/versioning is unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% — form_id has no description or enum — so the description must carry the full burden, and it does: it enumerates the three supported values (SAL_Quotation / SAL_SaleOrder / PUR_PurchaseOrder) and explains the fallback behavior for any other value.

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 (获取单据的「已验证 model 骨架」模板) and spells out exactly what the return contains: correct field names, required fields, required entry-line fields, and a model sample with placeholders. It also names the concrete form_ids it serves, so an agent can distinguish it from sibling field/query tools without opening the schema.

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 establishes a clear workflow: use placeholders like <客户编码>, substitute business data, skip field exploration, and validate with kingdee_validate_bill before saving. It also notes that unsupported forms return a hint. It stops short of explicitly contrasting itself with kingdee_get_fields or kingdee_list_forms, so the when-not context is implied rather than stated.

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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