Open source alternatives to experimental-design
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 experimental-design
experimental-design
Designs experiments and studies BEFORE data is collected
experimental-design is an agent skill for planning experiments and studies before any data is collected. It helps choose a design, randomise assignments, block units, and lay out the treatment combinations, so the results can answer the question you care about. The skill is built on three ideas. Randomisation assigns treatments at random so that known and unknown confounders are balanced in expectation, which is what turns a comparison into a causal claim. Replication means independent repetition at the right level, so you can estimate variability, and the skill names pseudoreplication, counting repeated measurements on one unit as independent replicates, as the most common fatal error. Blocking groups similar units, such as by batch, day, site or litter, and randomises within the blocks, which removes known nuisance variation from the noise. The skill then helps you pick among design types and generate the actual randomisation or designed-experiment layout with reproducible scripts. It warns against structural mistakes that make data uninterpretable, and it notes that no analysis can rescue a confounded design afterwards.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/experimental-design