Open source alternatives to ml-pipeline
24 open source AI Skills apps to use instead, best rated first.
Top picks
- G
github-ops
Launchgithub-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
Launchopensource-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
Launchandrej-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
Launchmarkitdown-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
Launchod-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
Launchgithub-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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Discovery, exploration, reporting and root cause analysis over Netdata metrics
Learn Claude Code
by shareAI-lab - A really interesting analysis of how coding agents like Claude
About ml-pipeline
ml-pipeline
Designs and implements production-grade ML pipeline infrastructure: configures
ml-pipeline is an agent skill from the jeffallan claude-skills collection for designing and implementing production machine learning pipeline infrastructure. Its listed coverage includes experiment tracking with MLflow or Weights and Biases, orchestration with Kubeflow or Airflow, feature engineering, distributed training and hyperparameter tuning. Its persona is a senior ML pipeline engineer. Its workflow runs in six stages. The agent maps the data flow and defines the interfaces between components, then validates the data schema and its distribution before any training starts, and halts and reports if the checks fail. It implements feature engineering with transformation pipelines, feature stores and validation checks. It configures distributed training, hyperparameter tuning and resource allocation. It logs metrics, parameters and artefacts so experiments can be compared and reproduced. The last stage runs model evaluation gates and proposes A/B testing or shadow deployment before a model is promoted. The skill suits ML engineers and platform teams who need repeatable training and deployment rather than notebooks. It is listed on skills.sh, where the page shows install counts and GitHub stars for the collection. Its Gen Agent Trust Hub audit is marked as failing, which the FAQ lists, while Socket and Snyk pass. Install it with npx skills add https://github.com/jeffallan/claude-skills --skill ml-pipeline.
- Price
- Free
- Made by
- jeffallan
- Category
- AI Skills
- Website
- github.com/jeffallan/claude-skills/ml-pipeline