Token导航 LogoToken导航TokenDH.com
开发敏感数据clawhub未标认证来源可访问clear审计提醒

invoice-scan发票扫描

Agent Skill

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。它适合让 Agent 生成配乐说明、整理音频流程、调用语音工具或处理播客和视频配音素材。使用时需要确认输入音频来源、输出格式、时长和模型限制;涉及人声克隆、版权音乐或公开发布时,应先核对授权和合规边界。

总安装

15,288

周安装

650

GitHub Stars

公开资料未说明

下载量

5,356
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:invoice-scan(发票扫描)
来源仓库:https://github.com/mr-muddle/invoice-scan
安装命令:
openclaw skills install invoice-scan
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install invoice-scan

简介

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。

  • 适用于人工智能驱动的发票 OCR 和数据提取。
  • 支持从发票图像、PDF 中进行文本提取和数据处理。
  • 使用时需确认输入音频来源、输出格式和模型限制,涉及文件读写时核对权限。
  • 安装命令为 openclaw skills install invoice-scan,建议确认权限范围和维护状态。

SKILL.md

name
invoice-scan
description
AI-powered invoice OCR, scanning, and data extraction. Use when: (1) user needs OCR or text extraction from invoice images, scanned documents, or PDFs, (2) scanning/reading invoices to extract structured data (JSON, CSV, Excel), (3) validating invoice arithmetic or classifying document types (invoice vs receipt vs other), (4) processing handwritten invoices, stamps, or multi-language documents (Chinese, Russian, European, etc.), (5) user asks to read/parse/extract/OCR an invoice or receipt. Keywords: OCR, invoice scanning, receipt scanning, document OCR, invoice data extraction, invoice parser, invoice reader. Works in two modes: agent-native (uses your own vision — no API key needed, only formatOutput for export) or CLI standalone (needs ANTHROPIC_API_KEY). Env: ANTHROPIC_API_KEY (CLI mode only). Install: npm install --production in scripts/.
metadata
clawdbot
requires
env
required
false
description
Anthropic API key (CLI mode only — not needed for agent-native mode)
bins
install
kind
shell
command
cd {SKILL_DIR}/scripts && npm install --production
label
Install Node.js dependencies (sharp, xlsx)
externalEndpoints
purpose
Send base64-encoded invoice images for AI vision extraction (CLI mode only)
dataTypes

Invoice Scan

⚠️ Privacy Notice

CLI mode sends base64-encoded invoice images to Anthropic's API (api.anthropic.com). Invoice data (supplier/buyer names, addresses, IBANs, bank details, amounts) will be transmitted to a third-party service. Confirm this is acceptable under your privacy and compliance requirements before use. Consider dedicated API credentials with usage limits.

Agent-native mode does NOT send data externally — the agent uses its own built-in vision. Only formatOutput() is called locally for CSV/Excel export.

Setup

Install dependencies (required before first use):

cd {SKILL_DIR}/scripts && npm install --production

Dependencies: sharp (image processing), xlsx (Excel export). Review scripts/package.json before installing.

CLI mode requires: ANTHROPIC_API_KEY environment variable. Agent-native mode requires: nothing — uses agent's built-in vision capability.

Two Modes

Mode 1: Agent-Native (No API Key, No External Calls)

Use your built-in vision to look at the invoice image directly. Do NOT call scanInvoice() — that function requires an API key and sends data externally. Instead:

  1. Look at the image with your vision capability
  2. Extract all fields into a JSON object matching the canonical schema in references/canonical-schema.md
  3. Classify document type: invoice, credit-note, receipt, purchase-order, delivery-note, confirmation, statement, other-financial, not-financial
  4. Validate arithmetic and business rules per references/validation-rules.md
  5. Present results (see Output Format below)
  6. For CSV/Excel export, construct the canonical JSON object and pass it to formatOutput() only:
const { formatOutput } = require('{SKILL_DIR}/scripts');
// invoiceData = the JSON object YOU built from your vision extraction
// IMPORTANT: include ALL fields from canonical-schema.md, including charges[]
// e.g. invoiceData.charges = [{ type: 'shipping', label: 'P&P', amount: 5.99, vatRate: 20, vatAmount: 1.20 }]
const csv = formatOutput(invoiceData, 'csv');    // string — local only
const xlsx = formatOutput(invoiceData, 'excel');  // Buffer — local only

Key: formatOutput() is purely local — no network calls, no API key needed. It just formats your extracted data into CSV or Excel.

Mode 2: CLI Standalone (Needs API Key)

For automation or pipelines. Requires ANTHROPIC_API_KEY env var.

ANTHROPIC_API_KEY=<key> node {SKILL_DIR}/scripts/cli.js scan <file> [--format json|csv|excel] [--output result.json]

Options: --provider claude, --accept strict|relaxed|any, --no-preprocess, --model <model>

Agent-Native Extraction Checklist

Extract ALL of:

Header: invoiceNumber, invoiceDate (YYYY-MM-DD), dueDate, currency (ISO 4217), supplierName, supplierAddress, supplierVatNumber, buyerName, buyerAddress, buyerVatNumber, paymentTerms, paymentReference, bankDetails (iban, bic, accountNumber, sortCode)

Line items: description, quantity, unitOfMeasure, unitPrice, lineTotal, vatRate, sku, discount

References: PO, contract, GRN, timesheet, project, proforma, invoice (original invoice if this is a credit/debit memo), credit-note, debit-note refs. For credit/debit memos, ALWAYS include the original invoice reference.

Totals: netTotal, vatBreakdown (rate + amount + type per band — type is the tax regime label e.g. "CGST", "SGST", "USt", "НДС", "IVA"), vatTotal, grossTotal, amountPaid, amountDue, discount (invoice-level discount amount), discountRate (percentage)

Metadata: paidDate (YYYY-MM-DD — date from PAID stamp), vatInclusive (true if line totals include VAT, false if net, null if unknown)

Charges: Surcharges/fees outside line items — shipping, postage, P&P, delivery, freight, carriage, dispatch, handling, insurance, eco-levy, surcharges. Each: type (shipping|handling|insurance|surcharge|discount|other), label (original text from document), amount, vatRate, vatAmount. Do NOT duplicate items already captured as line items.

Document type: documentType (invoice, credit-note, debit-note, receipt, purchase-order, delivery-note, confirmation, statement, other-financial, not-financial)

Additional: handwritten notes, stamps/seals (type + text), remarks/comments, document language (ISO 639-1)

Arithmetic Validation

  1. qty × unitPrice = lineTotal (per line)
  2. Sum of lineTotals = netTotal
  3. netTotal + vatTotal = grossTotal

(Tolerance: ±0.02 for rounding)

Locale Numbers

Parse regional formats automatically: US/UK (1,234.56), European (1.234,56), French (1 234,56), Indian (1,23,456.78). Use currency/country context when ambiguous.

Quality Score

Count present from: invoiceNumber, invoiceDate, currency, supplierName, buyerName, supplierVatNumber, netTotal, vatTotal, grossTotal. Score = present / 9. good ≥ 0.8, partial ≥ 0.5, poor < 0.5.

Output Format

📄 Invoice #{number} | {date}
   Supplier: {name} → Buyer: {name}
   Net: {currency}{net} | VAT: {currency}{vat} | Gross: {currency}{gross}
   [if charges exist] 📦 Charges: {label} {currency}{amount} [per charge]
   [if amountDue is not null] Amount Due: {currency}{amountDue} [if amountPaid] (Paid: {currency}{amountPaid})
   Items: {count} | Arithmetic: ✅/❌ | Quality: {rating} ({score}/9)

List warnings/flags, then offer: "Want JSON, CSV, or Excel?"

File Delivery

  • Output directory: {WORKSPACE}/invoice-scan/output/ (create if needed)
  • Naming: {supplierName}_{invoiceNumber}_{invoiceDate}.{ext} (replace spaces/slashes with hyphens)
  • Always save JSON automatically, offer CSV/Excel on request
  • Send file as chat attachment + confirm path

References

  • Full schema: references/canonical-schema.md
  • Validation rules: references/validation-rules.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

78.99%
按下载量换算4,231

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills