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adambbhe

kingdee_star

by adambbhe

kdy_fill_reimbursement

Creates reimbursement drafts from validated invoice data for Kingdee Cloud Star. Uses dry-run checks to catch issues before manual payment and approval steps.

Instructions

发票代填报销单草稿(受控写入)。 invoices: [{invoice_no,total,category_hint?,kind?,title?,face_tax?,face_net?,passenger?,fuel?}, ...] 默认 dry_run=True(只构造并过守卫,不真正提交);付款/提交审批仍人工。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo
invoicesYes
applicantYes
trip_form_idYes
cost_category_idNo
Behavior3/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It explains that dry_run defaults to true, meaning the tool only constructs and passes guards without actual submission, which is important behavioral context. However, it does not state what the tool returns (e.g., the constructed draft object or an ID), nor whether any side effects occur when dry_run=false. The safety info is partially conveyed but incomplete.

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 concise and front-loaded with the core purpose. It uses two sentences and a compact parameter list, avoiding any filler. Every piece of information serves a functional role, from the controlled-write label to the dry_run default. It is appropriately sized for the tool's complexity.

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 tool has several parameters, including a nested structured array, and no output schema. The description provides enough insight into the main data structure (invoices) and the dry_run behavior, but it omits details about the other three parameters and the expected return value. Given the complexity, an agent might struggle to correctly populate 'trip_form_id' or 'cost_category_id' without further clarification. Overall, the description is adequate but leaves notable gaps.

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?

With 0% schema description coverage, the description must compensate. It provides detailed semantics for the 'invoices' array by listing expected fields (invoice_no, total, category_hint, etc.) and clarifies the 'dry_run' parameter's role. However, it gives no explanation for 'applicant', 'trip_form_id', or 'cost_category_id', leaving agents to infer their meaning from names alone. While it covers some parameters well, it misses others.

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 a specific verb and resource: 'fill reimbursement draft' (发票代填报销单草稿). It also labels the operation as 'controlled write' (受控写入), which distinguishes it from read-only tools like kdy_list_invoice or kdy_get_reimb_detail. The purpose is unambiguous and not a mere restatement of the name.

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?

The description provides minimal guidance on when to use this tool versus alternatives. It mentions the default dry_run behavior and that payment/submission remains manual, but it does not explain when an agent should choose this tool over others, nor does it specify conditions that make it inappropriate. There is no explicit 'use this when...' or 'avoid if...' guidance.

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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