neurokit2
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
npx skills add K-Dense-AI/scientific-agent-skills --skill neurokit2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# NeuroKit2 ## Scope and evidence cutoff Use this skill for method-aware, reproducible biosignal research with NeuroKit2. The snapshot was checked on **2026-07-23** 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 tag `v0.2.13`; - 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 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 NeuroKit2 is a research and educational toolbox. Do **not** present its output as: - a diagnosis, treatment recommendation, patient-monitoring decision, or alarm; - validation, certification, or regulatory evidence for a medical device; or - proof that a physiological construct is measured validly in a new sensor, protocol, environment, population, or disease group. Validate acquisition hardware, electrode/optode placement, units, sampling and clock accuracy, preprocessing, detector/decomposition method, po
- Scope and evidence cutoff
- Boundary
- Reproducible installation
- Required data contract
- Core workflow
- 1. Inspect before transforming
- 2. Preserve preprocessing order
- 3. Treat schemas as runtime observations
- Current patterns
- ECG, corrected peaks, and duration-aware HRV
- EDA with explicit decomposition
- Events, epochs, and baseline
- RSA and multimodal processing
- Complexity returns values plus metadata
uv pip install "neurokit2==0.2.13" python skills/neurokit2/scripts/inspect_signal.py \ python skills/neurokit2/scripts/ecg_hrv_pipeline.py \ python skills/neurokit2/scripts/eda_pipeline.py \ python skills/neurokit2/scripts/plan_epochs.py \ python skills/neurokit2/scripts/validate_multimodal.py \ python skills/neurokit2/scripts/generate_synthetic.py \
What does the neurokit2 skill do?
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
How do I install it?
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill neurokit2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From K-Dense-AI/scientific-agent-skills, a repository with 32,619 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.