bambu-studio-ai
Bambu Lab 3D printer control and automation. Activate when user mentions: printer status, 3D printing, slice, analyze model, generate 3D, AMS filament, print monitor, Bambu Lab, or any 3D printing task. Full pi...
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.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install fdocr/clawshierInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Process receipt and invoice photos into structured expenses and log them to Google Sheets.
Activate this skill when the user sends a photo or image and any of these apply:
Do not activate for images that are clearly not financial documents (memes, screenshots of conversations, etc.).
Run each step sequentially. If a step fails, retry it up to 2 times before reporting the error.
Save the received image to a temporary file, then extract text:
node skills/receipt_ocr/handler.js --image <path_to_image>
Output schema:
{ "ocr_text": "STARBUCKS\n123 Main St..." }
Pipe the OCR output to the structurer:
echo '<step1_output>' | node skills/expense_structurer/handler.js
Output schema:
{
"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"
}
Pipe the structured expense to the validator:
echo '<step2_output>' | node skills/expense_validator/handler.js
This step:
vendor + date + total
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):
{
"date": "2026-03-05",
"vendor": "Starbucks",
"items": [...],
"subtot...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
OpenClaw skill that processes receipt/invoice photos from any chat channel, extracts expense data via OpenAI Vision, and logs it to a Google Spreadsheet.
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).
.env
Copy SKILL.md into your OpenClaw skills directory or install via ClawHub.
MIT
# 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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