Data Preprocessing Pipeline
Automated data preprocessing and cleaning pipelines
- Type
- Plugin
- Repository
- jeremylongshore/tons-of-skills-marketplace
- GitHub stars
- 2.8k
- License
- MIT
- Repo last updated
- Sep 27, 2026
- Version
- 1.23.0
- Author
- Claude Code Plugins
What Data Preprocessing Pipeline is
Data Preprocessing Pipeline is a plugin published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”
A plugin is a package that bundles skills, slash commands, subagents, hooks, and MCP connectors so they install together. Plugins are plain files with a manifest at .claude-plugin/plugin.json, and they work in both Claude Code and Claude Cowork.
Installing Data Preprocessing Pipeline adds everything it ships in one step. Connectors inside a plugin still need to be connected separately, and hooks and subagents only run in Cowork and Claude Code, not in regular chat.
How to install Data Preprocessing Pipeline
Claude Code
- Add the repository as a plugin marketplace: claude plugin marketplace add jeremylongshore/tons-of-skills-marketplace
- Install the plugin: claude plugin install data-preprocessing-pipeline@<marketplace-name>, using the marketplace name from the repository's .claude-plugin/marketplace.json.
- Restart the session if the new skills or commands don't appear straight away.
Claude Cowork
- Open Customize → Plugins and choose Add marketplace.
- Enter jeremylongshore/tons-of-skills-marketplace (the owner/repo shorthand works for GitHub).
- Find Data Preprocessing Pipeline in the list, click Install, then connect any connectors it needs from its Connectors tab.
New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.
Inside the source file
An excerpt from plugins/ai-ml/data-preprocessing-pipeline/.claude-plugin/plugin.json, shared under the repository's MIT license. Read the full file on GitHub.
Automated data preprocessing and cleaning pipelines
Installation
/plugin install data-preprocessing-pipeline@claude-code-plugins-plusUsage
/preprocessFeatures
- Automated workflows
- Best practices implementation
- Performance optimization
- Error handling
Requirements
- Python 3.8+
- Standard ML libraries
License
MIT
Before you install
- Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
- Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
- Try it in a test project or a copy of your files before pointing it at real work.
- Pin the version you tested, and review changes before updating.
- Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.
FAQ
What is Data Preprocessing Pipeline?
Data Preprocessing Pipeline is a plugin for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Automated data preprocessing and cleaning pipelines
How do I install Data Preprocessing Pipeline in Claude Code?
Add the repository as a plugin marketplace: claude plugin marketplace add jeremylongshore/tons-of-skills-marketplace Install the plugin: claude plugin install data-preprocessing-pipeline@<marketplace-name>, using the marketplace name from the repository's .claude-plugin/marketplace.json. Restart the session if the new skills or commands don't appear straight away.
Can I use Data Preprocessing Pipeline in Claude Cowork?
Open Customize → Plugins and choose Add marketplace. Enter jeremylongshore/tons-of-skills-marketplace (the owner/repo shorthand works for GitHub). Find Data Preprocessing Pipeline in the list, click Install, then connect any connectors it needs from its Connectors tab.
Is Data Preprocessing Pipeline safe to install?
It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.
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