Open source alternatives to arboreto
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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by shareAI-lab - A really interesting analysis of how coding agents like Claude
About arboreto

arboreto
Infers candidate gene regulatory networks
arboreto is an agent skill for inferring candidate gene regulatory networks from bulk or single-cell expression data, using the Arboreto library's GRNBoost2 and GENIE3 methods. GRNBoost2 uses stochastic gradient boosting regressions, and GENIE3 uses random forests. Each target gene is predicted from candidate regulators, excluding itself, to rank regulator-target associations. The skill is clear about what these results mean: they are observational predictive associations, not proof of direct binding, activation, repression or causal regulation. It also warns about the library's state. The latest PyPI release it checked was 0.1.6 from February 2021, and the Read the Docs site labels its docs 0.1.5, while the current GitHub source contains fixes that are not in the PyPI wheel. So an unpinned installation may not run inference, and the skill lists an exact stack that passed its smoke tests on macOS arm64 with Python 3.11. A reference file covers distributed computing. Use it when you need candidate regulators for a set of genes from expression data. It is part of the k-dense-ai scientific agent skills repository on GitHub, and the listing shows it as free.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/arboreto











