
Neurokit2
If you're processing physiological signals like ECG, EEG, or EDA data, this is a solid all-in-one toolkit. It handles the full pipeline from cleaning raw signals to extracting metrics like heart rate variability across time/frequency/nonlinear domains, EEG frequency band power, skin conductance responses, and respiratory patterns. The standout feature is how it integrates complexity analysis (entropy measures, fractal dimensions, Lyapunov exponents) directly into biosignal workflows, which usually requires stitching together multiple libraries. Works well for psychophysiology research, clinical applications, or any project where you need to go from messy sensor data to interpretable physiological metrics without reinventing standard preprocessing chains.
- skills.sh installs
- 2K
- GitHub stars
- 56.6K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add k-dense-ai/scientific-agent-skills --skill neurokit2 --agent claude-codeInstalls into .claude/skills of the current project.
Files
NeuroKit2
Scope and evidence cutoff
Use this skill for method-aware, reproducible biosignal research with NeuroKit2. The snapshot was checked on 2026-10-01 against:
- stable PyPI 0.2.13, released 2026-03-02;
- Python metadata (
>=3.10; classifiers 3.10–3.14) and wheel dependencies; - GitHub release notes/tags,
NEWS.rst, source at tagv0.2.13; - official API pages/examples (the live site identified itself as
0.2.13.dev214); and - pinned 0.2.13 runtime signatures and synthetic output schemas.
The current wheel requires pandas<3.0.0. The refreshed core checks use Python 3.13,
NumPy 2.5.3, and pandas 2.3.3; forcing pandas 3 conflicts with upstream metadata.
API fragments below assume caller-provided arrays and imports. Optional MNE source
reconstruction, cvxEDA, EMD, and pyRQA paths are source-reviewed, not runtime-validated
by this refresh. Synthetic checks establish software behavior, not empirical validity.
The live documentation can be ahead of the stable wheel. Prefer the pinned runtime for reproducible work and name both versions if consulting development docs.
Boundary
Sponsors
Details
- Repository
- github.com/k-dense-ai/scientific-agent-skills
- Categories
- DevOps & CI/CD, AI & Agent Building, Data Science & ML
- First seen
- Jun 3, 2026