A sophisticated rewards optimization engine that helps you maximize cashback, points, and miles by recommending the best card for every specific purchase.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install card-optimizer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install card-optimizer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Card Optimizer?
The Card Optimizer is a technical framework designed for Openclaw Skills to manage and optimize personal credit card portfolios. It moves beyond simple lists by providing an algorithmic approach to rewards, calculating the best card to use based on merchant categories, network acceptance, and current spending caps. It helps users navigate the complexity of rotating categories and varying point valuations to ensure every dollar spent earns the maximum possible return.
By maintaining a localized data structure, this skill offers privacy-first financial management. It empowers users of Openclaw Skills to conduct deep ROI analysis on annual fees and identify spending gaps where a new card could significantly increase their annual rewards yield. Whether you are a cashback enthusiast or a travel hacker, this tool provides the logic needed to treat your wallet like a professional portfolio.
Card Optimizer Use Cases
- Determining the optimal card for a specific merchant like Costco, Amazon, or a local restaurant.
- Tracking rotating 5% categories for cards like Chase Freedom Flex or Discover It.
- Evaluating whether a high annual fee card is actually profitable based on your specific spending patterns.
- Identifying which spending categories are currently under-optimized and would benefit from a new card application.
How Card Optimizer Works
- The skill parses a local JSON database containing your card's reward structures, network types, and spending caps.
- When a purchase is mentioned, it performs fuzzy category matching to identify the correct merchant type.
- It calculates the effective reward rate by factoring in cents-per-point (CPP) valuations and remaining balances on spending caps.
- It returns a recommendation including a primary card, the expected reward rate, and a secondary fallback card in case of network acceptance issues.
Card Optimizer Setup
To get started with this skill for Openclaw Skills, initialize your local data directory and create your card database:
mkdir -p data/card-optimizer
# The skill will guide you through creating cards.json on first run
You will need to list your cards, their reward rates, and optionally your estimated monthly spending to enable the advanced ROI and gap analysis features.
Card Optimizer Data Schema & Taxonomy
The skill organizes data within data/card-optimizer/cards.json using the following schema:
| Field | Description |
|---|---|
id |
Unique identifier for the credit card |
issuer |
The bank or company that issued the card |
network |
Visa, Mastercard, Amex, or Discover |
point_valuation_cpp |
Cents-per-point value for travel and transfer partners |
categories |
Array of reward rates, spending caps, and timeframes |
estimated_monthly_spending |
User-defined estimates used for ROI and gap analysis |
Card Optimizer Advanced Features
- Cap-Aware Logic: Automatically tracks when you are nearing spending limits on high-reward categories and suggests a pivot card.
- Network Intelligence: Specifically handles merchant-specific constraints, such as Visa-only requirements at Costco warehouses.
- ROI Auditing: Performs a break-even analysis on annual fees to suggest downgrades for cards that are costing more than they earn.
- Quarterly Automation: Manages activation status and category shifts for rotating reward cards within the Openclaw Skills environment.
SKILL.md
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