Overview
- Skill Key
- fdocr/clawshier
- Author
- fdocr
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/fdocr/clawshier
- Latest Commit SHA
- fb7914e93c3efa9b36e368a75c76bf5db59b2535
Scan receipt or invoice photos sent via chat, extract expense data using OpenAI Vision, validate and deduplicate, then log to a Google Spreadsheet. Responds with a short summary of what was added.
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Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 clawshier 技能。 若已安装,则直接安装 clawshier 技能。
# Receipt Expense Tracker
Process receipt and invoice photos into structured expenses and log them to Google Sheets.
## When to Activate
Activate this skill when the user sends a **photo or image** and any of these apply:
- The message mentions receipts, invoices, expenses, or purchases
- The image appears to be a receipt, invoice, or bill
- The user asks to log, track, or record an expense
- The user asks to add something to their expense spreadsheet
Do **not** activate for images that are clearly not financial documents (memes, screenshots of conversations, etc.).
## Pipeline
Run each step sequentially. If a step fails, retry it up to **2 times** before reporting the error.
### Step 1 — OCR
Save the received image to a temporary file, then extract text:
```bash
node skills/receipt_ocr/handler.js --image <path_to_image>
```
Output schema:
```json
{ "ocr_text": "STARBUCKS\n123 Main St..." }
```
### Step 2 — Structure
Pipe the OCR output to the structurer:
```bash
echo '<step1_output>' | node skills/expense_structurer/handler.js
```
Output schema:
```json
{
"date": "2026-03-05",
"vendor": "Starbucks",
"items": [
{ "description": "Caffe Latte", "quantity": 1, "amount": 5.95 }
],
"subtotal": 5.95,
"tax": 0.52,
"total": 6.47,
"currency": "USD",
"category": "Food & Drink"
}
```
### Step 3 — Validate
Pipe the structured expense to the validator:
```bash
echo '<step2_output>' | node skills/expense_validator/handler.js
```
This step:
- Generates a SHA-256 fingerprint from `vendor + date + total`
- Checks Google Sheets for duplicate fingerprints
- Normalizes currency codes and trims whitespace
- Validates all required fields are present
If a **duplicate is found**, stop the pipeline and tell the user:
> "This receipt appears to already be logged (vendor, date, total match an existing entry). Skipping."
Output schema (adds `fingerprint` field):
```json
{
"date": "2026-03-05",
"vendor": "Starbucks",
"items": [...],
"subtot...
# Clawshier OpenClaw skill that processes receipt/invoice photos from any chat channel, extracts expense data via OpenAI Vision, and logs it to a Google Spreadsheet. ## Prerequisites - Node.js 18+ - OpenAI API key - Google Cloud service account with Sheets API enabled ## Install ```bash git clone https://github.com/YOUR_USER/clawshier.git cd clawshier npm install cp .env.example .env ``` Fill in `.env` with your credentials (see `.env.example`). ### Google Sheets setup 1. Create a Google Cloud service account and download the JSON key file 2. Enable the Google Sheets API in your project 3. Create a spreadsheet and share it with the service account email 4. Add the spreadsheet ID and key file path to `.env` ### OpenClaw usage Copy `SKILL.md` into your OpenClaw skills directory or install via ClawHub. ## License MIT
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