Skills Guide

TaxHacker Receipt Analysis

VerifiedCaution

Extracts structured financial data from receipt/invoice images using AI.

Download and use
Sby Skills Guide Bot
Data & AIIntermediate
7/25/2026
#receipt-analysis#invoice-processing#ocr#expense-tracking

Recommended for

Data scientistData & analysis

Automated summary

Extracts structured financial data from receipt and invoice images using OCR or AI vision.

Strengths

  • Automated extraction of vendor name, date, total, tax, and line items
  • Local OCR mode to save API tokens
  • Built-in risk assessment
  • Flexible configuration via environment variables or CLI arguments

Limitations

  • Requires an API key for vision mode (unless using local OCR)
  • Output quality depends on image clarity
  • Only supports JPG, PNG, and WebP formats
When to use it

To quickly digitize and categorize expenses from receipt photos.

When not to use it

If images are blurry or low-resolution, or if you need a fully offline solution without any LLM API.

Security analysis

Caution
Quality score90/100

The skill runs a Python script to analyze receipt images, which involves file access and potential external API calls. This poses a moderate risk of sensitive data exposure, but no destructive actions are instructed.

Findings
  • •Executes Python script with user-provided file path
  • •May upload receipt images to external AI service using API keys
  • •Environment variables could expose API credentials
How this analysis is made

Examples

Analyze a receipt
Analyze the receipt at C:/Users/Docs/receipt_123.jpg and tell me the total amount.
Extract item list
Extract all item names and prices from the invoice image /home/user/invoice.png.
Risk assessment
Assess the risk of the receipt at receipts/dinner_2025.jpg and explain any anomalies.

TaxHacker Receipt Analysis Skill

Extract structured financial data from receipt/invoice images using AI.

Description

This skill analyzes images of receipts, invoices, or bills to extract key accounting information including vendor name, date, total amount, currency, tax, and itemized lists. It also provides an AI-based risk assessment and categorization.

Configuration (OpenClaw)

This skill is optimized for OpenClaw. If you have configured a model in OpenClaw, the skill can automatically use its settings.

  • If OPENCLAW_LLM_API_KEY is set in the environment, the skill will use it.
  • If OPENCLAW_LLM_BASE_URL is set, the skill will use it.
  • If OPENCLAW_LLM_MODEL is set, the skill will use it (e.g., gpt-4o, gpt-4o-mini).

Otherwise, you can provide parameters directly via CLI:

# Vision Mode (Default)
python -m tax_hacker_skill.skill "<file_path>" --api-key "YOUR_KEY" --model "gpt-4o-mini"

# Local OCR Mode (Saves tokens, no image upload)
python -m tax_hacker_skill.skill "<file_path>" --local-ocr

# Local OCR Mode with CnOCR
python -m tax_hacker_skill.skill "<file_path>" --local-ocr --ocr-engine cnocr

Parameters

  • file_path: (Required) Absolute path to the receipt image file (jpg, png, webp).
  • --api-key: (Optional) Override API Key.
  • --base-url: (Optional) Override API Base URL.
  • --model: (Optional) Override LLM Model.
  • --local-ocr: (Optional) Use local OCR instead of vision.
  • --ocr-engine: (Optional) OCR engine: auto, easyocr, cnocr.

Instructions

  1. Ensure the user has provided an image file path.
  2. Execute the following command to process the receipt: 
    python -m tax_hacker_skill.skill "<file_path>"
  3. The command will output a JSON object containing the extracted data.
  4. Use the output to update accounting records, generate reports, or answer user queries about their expenses.

Example Usage

"Analyze the receipt at C:/Users/Docs/receipt_123.jpg and tell me the total amount." -> Run: python -m tax_hacker_skill.skill "C:/Users/Docs/receipt_123.jpg"

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/taxhacker-receipt-analysis-mryiqh9c/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/taxhacker-receipt-analysis-mryiqh9c' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/taxhacker-receipt-analysis-mryiqh9c/download' --output '.skill-downloads/taxhacker-receipt-analysis-mryiqh9c/SKILL.md.part' && mv '.skill-downloads/taxhacker-receipt-analysis-mryiqh9c/SKILL.md.part' '.skill-downloads/taxhacker-receipt-analysis-mryiqh9c/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/taxhacker-receipt-analysis-mryiqh9c/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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