Use Case
Spark Engineer isn't just for solo use β teams can share skills and build consistent AI workflows across the organization. Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics. This guide covers how to deploy Spark Engineer for your team, standardize prompts, and create shared workflows that everyone can use.
Install Spark Engineer in your project directory: .claude/skills/spark-engineer/
Commit the skill folder to your repository so the whole team has access
Document your team's standard prompts in a shared README
Use Spark Engineer in code reviews, standups, and planning sessions
Iterate: collect feedback from the team and refine your prompts
Copy these prompts and use them with your AI agent after installing Spark Engineer
How can my team use Spark Engineer together?
Set up Spark Engineer for our project so everyone can use it
Create a shared workflow using Spark Engineer for our team
Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install spark-engineerOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install spark-engineerβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/spark-engineer/π‘Extract and place the folder at the path above, then restart your agent.