Open source alternatives to data-quality-frameworks
24 open source AI Skills apps to use instead, best rated first.
Top picks
- G
github-ops
Getgithub-ops is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It manages a GitHub repository with a focus on community health, CI reliability and the experience of contributors. It covers triaging issues by classify
Open source
- O
opensource-pipeline
Getopensource-pipeline is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It prepares a private project for safe public release through a three-stage pipeline. The fork stage strips secrets from a copy. The sanitise st
Open source
- A
andrej-karpathy-skills
Getandrej-karpathy-skills is a single CLAUDE.md file from the multica-ai project that is meant to improve how Claude Code behaves on coding tasks. It is derived from Andrej Karpathy's public observations about LLM coding pitfalls. The file dis
Open source
- M
microsoft/markitdown
Getmarkitdown-mcp is the MCP server package for MarkItDown, Microsoft's tool for converting many file formats to Markdown for language models. It is a lightweight server that runs over stdio, Streamable HTTP or SSE, and exposes one tool, conve
Open source
- O
od-contribute
Getod-contribute is an agent skill in the OpenDesign project that provides a guided, one-click contribution flow to the OpenDesign repository, written so that people without a coding background can send a real pull request. It is locked to the
Open source
- G
github-deep-research
Getgithub-deep-research is an agent skill from the DeerFlow project that researches a single GitHub repository in several rounds and writes a report in Markdown. It is for requests that need more than a README summary, such as a comprehensive
Open source
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About data-quality-frameworks
data-quality-frameworks
Implement data quality validation
data-quality-frameworks is an agent skill from the wshobson/agents collection for building data quality validation into data pipelines. It covers three tools and approaches: Great Expectations for validating datasets against expectations, dbt tests for checking transformed models, and data contracts that set agreed rules between the teams that produce and consume data. The skill begins with the core dimensions of data quality, which give the checks a shared vocabulary, and then gives patterns for building the checks into a pipeline so bad data is caught before it reaches reports or models. Its uses include implementing data quality checks in pipelines, setting up Great Expectations validation, building comprehensive dbt test suites, establishing data contracts between teams, monitoring quality metrics over time, and running data validation automatically in CI/CD. It is written for data engineers and analytics engineers who want quality rules to live in code and run on every change rather than be checked by hand. The skill is installed with the skills CLI from the wshobson/agents repository. Its skills.sh page showed about 11.0K installs and passing results from three security audits at the time of the scan.
- Price
- Free
- Made by
- wshobson
- Category
- AI Skills
- Website
- github.com/wshobson/agents/data-quality-frameworks