Self-hosted alternatives to explore-data
5 self-hosted AI Skills apps to use instead, best rated first.
Top picks
- C

claude-to-deerflow
Launchclaude-to-deerflow is an agent skill that lets an assistant send messages and questions to a running DeerFlow instance through its HTTP API. DeerFlow is an AI agent platform built on LangGraph that orchestrates sub-agents for research, code
Self-hosted
- O

open-notebook
Launchopen-notebook is an agent skill for organising research with Open Notebook, a self-hosted alternative to NotebookLM. It arranges sources, notes and AI conversations into research notebooks. Sources can be PDFs, web pages, audio, video and O
Self-hosted
- R

Reactive Resume
LaunchReactive Resume is a free and open-source resume builder for writing resumes and cover letters, checking the work, and tracking job applications. You create a free account, import an existing resume or start from scratch, and see the finish
Open sourceSelf-hosted
- S

self-hosted-funnel-launch
LaunchSelf-hosted funnel launch is an agent skill that takes a funnel from an empty install to published on infrastructure you control, using the Autonnel funnel builder, which is licensed Apache-2.0. The result covers a landing page, checkout, a
Self-hosted
- G

get-convex/convex-backend
LaunchConvex is an open-source reactive database for web app developers. It combines a database, a place to write server functions in pure TypeScript, and client libraries that keep the app's data live, so screens update as the data changes. Beca
Self-hosted
About explore-data

explore-data
Profile and explore a dataset to understand its shape, quality, and patterns
explore-data is a command from Anthropic's knowledge-work plugins, listed on skills.sh. It profiles a dataset to understand its shape, quality and patterns before any analysis begins. It is used when a new table or file is encountered, to check null rates, column distributions and the way the data is structured. The command is run with /explore-data followed by a table name or a file. Its workflow starts by accessing the data: if a data warehouse connection is available, the command reads the table through it, and otherwise it works from an uploaded file. A connectors guide explains which tools are connected. It suits analysts who receive unfamiliar data and want to know what is in it, where its gaps are, and whether it can be trusted, before they answer any question with it.
- Price
- Free
- Made by
- anthropics
- Category
- AI Skills
- Website
- github.com/anthropics/knowledge-work-plugins/explore-data