pci-compliance

wshobson/agents · updated Apr 8, 2026

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$npx skills add https://github.com/wshobson/agents --skill pci-compliance
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summary

Implement PCI DSS compliance requirements for secure payment card handling.

  • Covers all 12 core PCI DSS requirements across network security, data protection, access control, monitoring, and policy
  • Provides practical code examples for tokenization (both processor-based and custom), encryption at rest and in transit, and audit logging
  • Includes data minimization rules specifying what card data can and cannot be stored, plus Luhn validation for card numbers
  • Outlines compliance levels
skill.md

PCI Compliance

Master PCI DSS (Payment Card Industry Data Security Standard) compliance for secure payment processing and handling of cardholder data.

When to Use This Skill

  • Building payment processing systems
  • Handling credit card information
  • Implementing secure payment flows
  • Conducting PCI compliance audits
  • Reducing PCI compliance scope
  • Implementing tokenization and encryption
  • Preparing for PCI DSS assessments

PCI DSS Requirements (12 Core Requirements)

Build and Maintain Secure Network

  1. Install and maintain firewall configuration
  2. Don't use vendor-supplied defaults for passwords

Protect Cardholder Data

  1. Protect stored cardholder data
  2. Encrypt transmission of cardholder data across public networks

Maintain Vulnerability Management

  1. Protect systems against malware
  2. Develop and maintain secure systems and applications

Implement Strong Access Control

  1. Restrict access to cardholder data by business need-to-know
  2. Identify and authenticate access to system components
  3. Restrict physical access to cardholder data

Monitor and Test Networks

  1. Track and monitor all access to network resources and cardholder data
  2. Regularly test security systems and processes

Maintain Information Security Policy

  1. Maintain a policy that addresses information security

Compliance Levels

Level 1: > 6 million transactions/year (annual ROC required) Level 2: 1-6 million transactions/year (annual SAQ) Level 3: 20,000-1 million e-commerce transactions/year Level 4: < 20,000 e-commerce or < 1 million total transactions

Data Minimization (Never Store)

# NEVER STORE THESE
PROHIBITED_DATA = {
    'full_track_data': 'Magnetic stripe data',
    'cvv': 'Card verification code/value',
    'pin': 'PIN or PIN block'
}

# CAN STORE (if encrypted)
ALLOWED_DATA = {
    'pan': 'Primary Account Number (card number)',
    'cardholder_name': 'Name on card',
    'expiration_date': 'Card expiration',
    'service_code': 'Service code'
}

class PaymentData:
    """Safe payment data handling."""

    def __init__(self):
        self.prohibited_fields = ['cvv', 'cvv2', 'cvc', 'pin']

    def sanitize_log(self, data):
        """Remove sensitive data from logs."""
        sanitized = data.copy()

        # Mask PAN
        if 'card_number' in sanitized:
            card = sanitized['card_number']
            sanitized['card_number'] = f"{card[:6]}{'*' * (len(card) - 10)}{card[-4:]}"

        # Remove prohibited data
        for field in self.prohibited_fields:
            sanitized.pop(field, None)

        return sanitized

    def validate_no_prohibited_storage(self, data):
        """Ensure no prohibited data is being stored."""
        for field in self.prohibited_fields:
            if field in data:
                raise SecurityError(f"Attempting to store prohibited field: {field}")

Tokenization

Using Payment Processor Tokens

import stripe

class TokenizedPayment:
    """Handle payments using tokens (no card data on server)."""

    @staticmethod
    def create_payment_method_token(card_details):
        """Create token from card details (client-side only)."""
        # THIS SHOULD ONLY BE DONE CLIENT-SIDE WITH STRIPE.JS
        # NEVER send card details to your server

        """
        // Frontend JavaScript
        const stripe = Stripe('pk_...');

        const {token, error} = await stripe.createToken({
            card: {
                number: '4242424242424242',
                exp_month: 12,
                exp_year: 2024,
                cvc: '123'
            }
        });

        // Send token.id to server (NOT card details)
        """
        pass

    @staticmethod
    def charge_with_token(token_id, amount):
        """Charge using token (server-side)."""
        # Your server only sees the token, never the card number
        stripe.api_key = "sk_..."

        charge = stripe.Charge.create(
            amount=amount,
            currency="usd",
            source=token_id,  # Token instead of card details
            description="Payment"
        )

        return charge

    @staticmethod
    def store_payment_method(customer_id, payment_method_token):
        """Store payment method as token for future use."""
        stripe.Customer.modify(
            customer_id,
            source=payment_method_token
        )

        # Store only customer_id and payment_method_id in your database
        # NEVER store actual card details
        return {
            'customer_id': customer_id,
            'has_payment_method': True
            # DO NOT store: card number, CVV, etc.
        }

Custom Tokenization (Advanced)

import secrets
from cryptography.fernet import Fernet

class TokenVault:
    """Secure token vault for card data (if you must store it)."""

    def __init__(self, encryption_key):
        self.cipher = Fernet(encryption_key)
        self.vault = {}  # In production: use encrypted database

    def tokenize(self, card_data):
        """Convert card data to token."""
        # Generate secure random token
        token = secrets.token_urlsafe(32)

        # Encrypt card data
        encrypted = self.cipher.encrypt(json.dumps(card_data).encode())

        # Store token -> encrypted data mapping
        self.vault[token] = encrypted

        return token

    def detokenize(self, token):
        """Retrieve card data from token."""
        encrypted = self.vault.get(token)
        if not encrypted:
            raise ValueError("Token not found")

        # Decrypt
        decrypted = self.cipher.decrypt(encrypted)
        return json.loads(decrypted.decode())

    def delete_token(self, token):
        """Remove token from vault."""
        self.vault.pop(token, None)

Encryption

Data at Rest

from cryptography.hazmat.primitives.ciphers.aead import AESGCM
import os

class EncryptedStorage:
    
how to use pci-compliance

How to use pci-compliance on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add pci-compliance
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/wshobson/agents --skill pci-compliance

The skills CLI fetches pci-compliance from GitHub repository wshobson/agents and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/pci-compliance

Reload or restart Cursor to activate pci-compliance. Access the skill through slash commands (e.g., /pci-compliance) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.740 reviews
  • Dhruvi Jain· Dec 28, 2024

    pci-compliance has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Yuki Lopez· Dec 28, 2024

    Solid pick for teams standardizing on skills: pci-compliance is focused, and the summary matches what you get after install.

  • Oshnikdeep· Nov 19, 2024

    Solid pick for teams standardizing on skills: pci-compliance is focused, and the summary matches what you get after install.

  • Yuki Sethi· Nov 19, 2024

    pci-compliance has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Oct 10, 2024

    We added pci-compliance from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kiara Ghosh· Oct 10, 2024

    Keeps context tight: pci-compliance is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sakshi Patil· Sep 21, 2024

    pci-compliance fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mia Okafor· Sep 17, 2024

    I recommend pci-compliance for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Isabella Iyer· Sep 17, 2024

    pci-compliance has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Yuki Ndlovu· Sep 5, 2024

    pci-compliance reduced setup friction for our internal harness; good balance of opinion and flexibility.

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