Ca File Processor

面向印度 CA 场景，自动识别 PDF、Excel、CSV、JPG/PNG 文件类型，调用对应脚本提取文本、表格和 GSTIN、发票号、金额、日期等字段；扫描件使用 OCR 并给出置信度，处理在本地完成。

purvik6062

热度 48.44

最近更新 2026-05-11 17:38:22

分类：效率依赖：代码执行 / 读写文件应用场景：数据处理 / 文件转换 / 财务

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add ca-file-processor

Metadata

name: ca-file-processor
description: Process financial documents for Indian CA firms. Use when any PDF, Excel (.xlsx/.xls), CSV, JPG, or PNG file is received or uploaded — including GST returns, ITR PDFs, scanned invoices, trial balance sheets, bank statements, Form 16, TDS certificates, and audit reports. Automatically detects file type and extracts text, tables, and key fields (GSTIN, invoice number, totals, dates). Triggers on: file upload, attachment, "process this file", "read this PDF", "extract from this invoice", "analyse this statement", "what does this document say".
version: 1.0.1
homepage: https://github.com/purvik6062/ca-file-processor
metadata: {"openclaw":{"emoji":"📂","requires":{"bins":["python3","tesseract"],"env":[]},"files":["scripts/*"]}}

CA File Processor

This skill processes the four most common file formats used by Indian CA firms and extracts structured information from them for analysis, summarisation, and answering queries.

Supported formats

PDF — GST returns, ITR acknowledgements, audit reports, scanned invoices (text-layer and scanned via OCR)
Excel (.xlsx / .xls) — Trial balance, P&L, balance sheets, payroll registers, GST workings
CSV — Bank statement exports (HDFC, ICICI, SBI), GSTR-2B downloads, Tally exports
Images (.jpg / .png) — WhatsApp invoice photos, scanned Form 16, cheque images

How to use

When a file is attached or uploaded, run the appropriate script:

python3 scripts/skill_router.py <file_path>

The router auto-detects the file type and calls the correct processor. It returns a structured JSON dict.

What to do with the output

Once the script returns output, use it to:

Answer the user's question about the document
Extract specific fields they asked for (GSTIN, totals, dates)
Summarise the document in plain language
Flag anomalies or missing information
Compare figures across multiple documents

Field extraction — what gets detected automatically

For invoices and PDFs:

GSTIN (supplier and recipient)
Invoice number and date
Total amount / grand total
PAN number
Email and phone

For bank statements (CSV):

Total debits and credits
Date range of transactions
Detected bank format

For Excel files:

Document type (trial balance / P&L / balance sheet / payroll / GST workings / ledger)
Sheet names and row counts
Preview of header rows

OCR notes

Text-layer PDFs are read directly (fast, accurate)
Scanned PDFs and images go through Tesseract OCR (English + Hindi)
Confidence is rated high / medium / low in the output
Always flag low-confidence results to the user and ask for confirmation on numeric fields

Trust statement

This skill runs entirely locally on your server. No data is sent to any external service. All processing happens via open-source Python libraries (PyMuPDF, pytesseract, openpyxl, pandas).