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WaHaiLong

Kingdee MCP Server

by WaHaiLong

kingdee_query_quality_inspections

Read-onlyIdempotent

Query incoming material inspection records to verify quality and decide on warehouse acceptance. Filter by document status or pass/fail quantities.

Instructions

查洵来料检验单(QIS_InspectBill/IQC)列表。

来料检验单用于对采购物料进行质量检验,判断是否允许入库。

常用 filter_string:

  • 已检验: "FDocumentStatus='C'"

  • 检验结果-合格: "FResult='1'" 或 "FPassQty>0"

  • 检验结果-不合格: "FFailQty>0"

推荐 field_keys: FID,FBillNo,FDate,FDocumentStatus,FSupplierId.FName,FMaterialId.FName,FPassQty,FFailQty,FInspectTypeId.FName

Returns: str: JSON 格式的来料检验单列表

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description confirms it is a list query, adding minimal behavioral insight beyond annotations. It does not contradict annotations, but offers no additional details about behavior (e.g., rate limits, data freshness).

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 structured with a concise first paragraph stating the purpose and a second paragraph with examples. It is front-loaded and efficient, though the examples could be more compact. No unnecessary repetition.

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

Completeness3/5

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

The description covers the tool's purpose and provides useful query patterns, but it lacks details about the output structure beyond 'JSON format'. Given that an output schema exists, the description is somewhat complete but could offer more context about the returned fields or pagination.

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

Parameters4/5

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

Although schema description coverage is 0%, the description enriches the schema by providing concrete examples of filter_string values and recommended field_keys. This adds significant practical meaning beyond the schema definitions (e.g., showing how to filter by result or pass/fail quantities).

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 clearly states the tool queries a list of incoming material inspection orders (QIS_InspectBill/IQC). It specifies the verb 'query' and the resource 'quality inspections', distinguishing it from other query siblings like kingdee_query_bills.

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

Usage Guidelines3/5

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

The description provides useful filter_string examples for common statuses (inspected, passed, failed) and recommended field_keys, which helps in constructing queries. However, it does not explicitly state when to prefer this tool over similar query tools (e.g., kingdee_query_bills) or when not to use it.

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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