neurokit2
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Builds and audits reproducible NeuroKit2 research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Use when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
- Package
- 20 files, 187 KB
- SKILL.md
- 1821 words, 12+ sections
- Code
- Python (7)
- Allowed tools
ReadWriteEditBashGlob- License
- MIT
- Compatibility
- Python 3.10+ and uv; pinned workflows use NeuroKit2 0.2.13. Core processing needs NumPy, SciPy, pandas<3, scikit-learn, matplotlib, PyWavelets, requests, and setuptools; selected EEG, cvxEDA, plotting, file-format, and RQA features need separately locked optional packages.
SKILL.md covers: NeuroKit2 · 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
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 15 KB |
references/bio_module.md | doc | 8.0 KB |
references/complexity.md | doc | 7.3 KB |
references/ecg_cardiac.md | doc | 7.0 KB |
references/eda.md | doc | 7.8 KB |
references/eeg.md | doc | 7.1 KB |
references/emg.md | doc | 6.8 KB |
references/eog.md | doc | 5.2 KB |
references/epochs_events.md | doc | 7.3 KB |
references/hrv.md | doc | 9.0 KB |
references/ppg.md | doc | 7.1 KB |
references/rsp.md | doc | 6.7 KB |
references/signal_processing.md | doc | 6.9 KB |
scripts/_common.py | script | 19 KB |
scripts/ecg_hrv_pipeline.py | script | 12 KB |
scripts/eda_pipeline.py | script | 10 KB |
scripts/generate_synthetic.py | script | 7.4 KB |
scripts/inspect_signal.py | script | 13 KB |
scripts/plan_epochs.py | script | 10 KB |
scripts/validate_multimodal.py | script | 14 KB |
External hosts referenced
doi.org neuropsychology.github.io github.com arxiv.org pubmed.ncbi.nlm.nih.gov sprweb.org export.arxiv.org pmc.ncbi.nlm.nih.gov pypi.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-neurokit2-scan.json
- Badge for your README:
- Request a re-scan