neurokit2

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

Quality

86%

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Securityby

Passed

No findings from the security scan

Quality

Content

80%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured, highly actionable skill body with excellent progressive disclosure into twelve verified reference files. The main weakness is missing validation/verification checkpoints in batch and multi-signal processing workflows.

Suggestions

Add explicit validation/verification steps to batch workflows (e.g., after nk.bio_process, check signal quality flags or assert expected channel presence before nk.bio_analyze) to lift workflow_clarity above the cap.

De-duplicate the HRV and bio_process code blocks that appear in both 'Core Capabilities' and 'Common Workflows', or cross-reference one from the other, to tighten conciseness.

Convert the 'Analysis Modes' section from an assertion into an instruction (how to force or detect event-related vs interval-related mode) so the workflow is actionable rather than descriptive.

Dimension	Reasoning	Score
Conciseness	The body is largely code-forward with no padding of concepts Claude already knows, but HRV and bio_process examples recur across both 'Core Capabilities' and 'Common Workflows', and the 12-item References section restates the inline reference pointers, leaving minor trim opportunities.	4 / 5
Actionability	Every section provides copy-paste-ready, executable Python with realistic sampling rates and parameters, and the Quick Start covers loading example data through analysis end-to-end.	5 / 5
Workflow Clarity	Processing sequences are shown (e.g., 'cleaning -> R-peak detection -> delineation -> quality assessment') but there are no validation or verification checkpoints for batch operations like bio_process, and the analysis-mode auto-selection is asserted rather than instructed, leaving checkpoint gaps.	3 / 5
Progressive Disclosure	The SKILL.md is a concise overview that signals twelve real one-level-deep reference files (e.g., 'See references/ecg_cardiac.md'), each verified to exist and self-contained with no nested pointer chains, making navigation easy.	5 / 5
	Total	17 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that clearly states both what the skill does and when to use it, with concrete modality and analysis-domain triggers. Minor gains possible from adding common synonyms (e.g., GSR) and signal-file extensions.

Dimension	Reasoning	Score
Specificity	The description enumerates seven concrete signal types (ECG, EEG, EDA, RSP, PPG, EMG, EOG) and six concrete analysis use-cases ('heart rate variability analysis, event-related potentials, complexity measures'), giving comprehensive coverage of concrete actions rather than vague language.	5 / 5
Completeness	It explicitly answers 'what' ('Comprehensive biosignal processing toolkit for analyzing physiological data') and 'when' with a dedicated 'Use this skill when processing...' clause listing concrete trigger scenarios, matching the top anchor.	5 / 5
Trigger Term Quality	It includes natural phrases users say ('heart rate variability', 'event-related potentials', 'electrodermal responses', 'respiratory patterns') and all seven modality acronyms, but omits common synonyms like 'GSR' and any file-extension/signal-file triggers that some users might cite.	4 / 5
Distinctiveness Conflict Risk	The biosignal/psychophysiology niche is clearly bounded with modality-specific triggers, making it unlikely to fire for unrelated skills; minimal conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: foryourhealth111-pixel/Vibe-Skills
Path: bundled/skills/neurokit2/SKILL.md
Commit: d5ae560

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.