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.

Quality

92%

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Securityby

Passed

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Quality

Content

92%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.

The content is highly actionable with a clear, validated workflow and excellent progressive disclosure to real bundle files. The only slight cost is conciseness from inline pinned version/date detail rather than a dedicated deprecated section.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence without explaining basic biosignal/library concepts, but it carries pinned time-sensitive detail (versions, dates) outside a dedicated deprecated/old-patterns section, a minor conciseness cost.	4 / 5
Actionability	It provides copy-paste-ready bash and python snippets with real flags across inspect, ECG/HRV, EDA, epochs, multimodal, and synthetic-fixture workflows, covering the common cases with executable commands.	5 / 5
Workflow Clarity	The 'Core workflow' gives an explicit numbered 10-step sequence with an 'Inspect before transforming' front checkpoint and validation scripts for batch/destructive operations, including feedback on resolving artifacts before proceeding.	5 / 5
Progressive Disclosure	SKILL.md is a clear overview that points one level deep to 12 verified reference files and 6 verified scripts via a well-signaled table, with content appropriately split and easy to navigate.	5 / 5
	Total	19 / 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.

The description is specific, complete, and distinctive, clearly stating what the skill does and when to use it with a concrete trigger and a useful negative boundary. Its only minor gap is trigger-term breadth, which is somewhat technical rather than colloquial.

Dimension	Reasoning	Score
Specificity	The description lists multiple concrete actions over a named domain ('build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity'), matching the comprehensive-coverage anchor.	5 / 5
Completeness	It explicitly answers both 'what' (build/audit reproducible research workflows for the listed analyses) and 'when' ('Trigger when code imports neurokit2 or needs its current APIs...') with concrete trigger phrases and a negative boundary.	5 / 5
Trigger Term Quality	It includes natural triggers like 'Trigger when code imports neurokit2' plus APIs/schemas/validation, but the keyword set is fairly technical and lacks casual synonyms a non-expert might say, leaving it just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	It targets a clear niche (NeuroKit2 physiological time-series) with distinct triggers and an explicit exclusion ('not for diagnosis or device validation'), giving minimal conflict risk with other skills.	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: K-Dense-AI/scientific-agent-skills
Path: skills/neurokit2/SKILL.md
Commit: 49c6e97

Reviewed: 9 days ago

Table of Contents

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