Expert guidance for financial systems, FinTech applications, banking platforms, and payment processing.
Works with
Covers payment gateway integration (Stripe), open banking APIs (Plaid), and core banking concepts including PCI-DSS, SOX, and Basel III compliance
Includes practical code examples for payment processing, refunds, webhook handling, and bank account/transaction retrieval
Provides financial calculation utilities for compound interest, loan amortization, NPV, and ROI with proper Decima
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfinance-expertExecute the skills CLI command in your project's root directory to begin installation:
Fetches finance-expert from personamanagmentlayer/pcl and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate finance-expert. Access via /finance-expert in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
3
total installs
3
this week
15
GitHub stars
0
upvotes
Run in your terminal
3
installs
3
this week
15
stars
Expert guidance for financial systems, FinTech applications, banking platforms, payment processing, and financial technology development.
# Payment gateway integration (Stripe)
import stripe
from decimal import Decimal
stripe.api_key = "sk_test_..."
class PaymentService:
def create_payment_intent(self, amount: Decimal, currency: str = "usd"):
"""Create payment intent with idempotency"""
return stripe.PaymentIntent.create(
amount=int(amount * 100), # Convert to cents
currency=currency,
payment_method_types=["card"],
metadata={"order_id": "12345"}
)
def process_refund(self, payment_intent_id: str, amount: Decimal = None):
"""Process full or partial refund"""
return stripe.Refund.create(
payment_intent=payment_intent_id,
amount=int(amount * 100) if amount else None
)
def handle_webhook(self, payload: str, signature: str):
"""Handle Stripe webhook events"""
try:
event = stripe.Webhook.construct_event(
payload, signature, webhook_secret
)
if event.type == "payment_intent.succeeded":
payment_intent = event.data.object
self.handle_successful_payment(payment_intent)
elif event.type == "payment_intent.payment_failed":
payment_intent = event.data.object
self.handle_failed_payment(payment_intent)
return {"status": "success"}
except ValueError:
return {"status": "invalid_payload"}
# Open Banking API integration (Plaid)
from plaid import Client
from plaid.errors import PlaidError
class BankingService:
def __init__(self):
self.client = Client(
client_id="...",
secret="...",
environment="sandbox"
)
def create_link_token(self, user_id: str):
"""Create link token for Plaid Link"""
response = self.client.LinkToken.create({
"user": {"client_user_id": user_id},
"client_name": "My App",
"products": ["auth", "transactions"],
"country_codes": ["US"],
"language": "en"
})
return response["link_token"]
def exchange_public_token(self, public_token: str):
"""Exchange public token for access token"""
response = self.client.Item.public_token.exchange(public_token)
return {
"access_token": response["access_token"],
"item_id": response["item_id"]
}
def get_accounts(self, access_token: str):
"""Get user's bank accounts"""
response = self.client.Accounts.get(access_token)
return response["accounts"]
def get_transactions(self, access_token: str, start_date: str, end_date: str):
"""Get transactions for date range"""
response = self.client.Transactions.get(
access_token,
start_date,
end_date
)
return response["transactions"]
from decimal import Decimal, ROUND_HALF_UP
from datetime import datetime, timedelta
class FinancialCalculator:
@staticmethod
def calculate_interest(principal: Decimal, rate: Decimal, periods: int) -> Decimal:
"""Calculate compound interest"""
return principal * ((1 + rate) ** periods - 1)
@staticmethod
def calculate_loan_payment(principal: Decimal, annual_rate: Decimal, months: int) -> Decimal:
"""Calculate monthly loan payment (amortization)"""
monthly_rate = annual_rate / 12
payment = principal * (monthly_rate * (1 + monthly_rate) ** months) / \
((1 + monthly_rate) ** months - 1)
return payment.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)
@staticmethod
def calculate_npv(cash_flows: list[Decimal], discount_rate: Decimal) -> Decimal:
"""Calculate Net Present Value"""
npv = Decimal('0')
for i, cf in enumerate(cash_flows):
npv += cf / ((1 + discount_rate) ** i)
return npv.Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
erichowens/some_claude_skills
sickn33/antigravity-awesome-skills
erichowens/some_claude_skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
I recommend finance-expert for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
finance-expert fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: finance-expert is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for finance-expert matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: finance-expert is focused, and the summary matches what you get after install.
finance-expert is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
finance-expert reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for finance-expert matched our evaluation — installs cleanly and behaves as described in the markdown.
finance-expert reduced setup friction for our internal harness; good balance of opinion and flexibility.
finance-expert has been reliable in day-to-day use. Documentation quality is above average for community skills.
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