Luca Assistant for Openclaw

A powerful credit card rewards optimization tool for tracking portfolios, monitoring bank application rules, and identifying the best sign-up bonuses.

troyt-666
v1.0.1
Mar 23, 2026
0
846
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install luca-assistant

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install luca-assistant 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 Luca Assistant?

Luca Assistant is a comprehensive technical solution for managing US credit card rewards and portfolio health. Operating as a sophisticated utility within the Openclaw Skills ecosystem, it allows users to query detailed information on over 150 credit cards, including category multipliers, annual credits, and current welcome offers. It is specifically designed to handle complex issuer logic like the Chase 5/24 rule and Amex lifetime language, ensuring users make informed application decisions.

By leveraging a local SQLite database, Luca Assistant provides high-performance access to card metadata sourced from reliable industry providers. The skill functions as an MCP (Model Context Protocol) server, enabling seamless integration with AI coding agents to automate the research, comparison, and tracking of financial products without manual data entry or fabrication.

Luca Assistant Use Cases

  • Comparing annual fees and earning multipliers between multiple premium travel cards.
  • Identifying the highest current sign-up bonuses worth a specific dollar amount.
  • Tracking personal credit card portfolios to calculate remaining Chase 5/24 slots.
  • Verifying bank-specific application rules before submitting a new card request.
  • Enriching local card data with updated earning rates found through web research.

How Luca Assistant Works

  1. The Openclaw Skills environment initializes the Luca Assistant MCP server and verifies the local environment.
  2. A local database is seeded with data for 150+ cards, including current offers and APRs from external sources.
  3. The agent invokes specific luca_ tools to query card details, compare benefits, or check portfolio status.
  4. If data gaps are identified, the agent uses enrichment workflows to update the local database via web search results.
  5. Portfolio changes (adding or closing cards) are persisted to the database to maintain an accurate 5/24 count and historical record.

Luca Assistant Setup

Ensure you have python3 and uv installed. To set up Luca Assistant within Openclaw Skills, run the following commands:

# Ensure local bin is in your path
export PATH="$HOME/.local/bin:$PATH"

# Run the installation and database seeding script
bash {baseDir}/scripts/setup.sh

# Verify the installation
luca-mcp --help
luca cards | head -5

Luca Assistant Data Schema & Taxonomy

Luca Assistant manages its data through a structured SQLite database located at ~/.local/share/luca/luca.db. The data is organized into three primary domains:

Domain Description Key Metadata
Card Registry General card data Bank, card name, fees, and base rewards
Offers Sign-up bonuses Minimum spend, bonus amount, and expiration
User Portfolio Personal card history Open date, closed date, limit, and 5/24 status
Benefits Earning multipliers Category, multiplier value, and point type

Luca Assistant Advanced Features

  • Direct MCP server integration for real-time agent interaction.
  • Automated Chase 5/24 status calculation based on user portfolio data.
  • Data enrichment hooks to manually or programmatically update category multipliers.
  • Multi-source data importing from Offer Optimist (SUBs) and CFPB (fees/APRs).
  • Integration compatibility with the Nitan skill for USCardForum community data points.

SKILL.md


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