Skills neuropixels-analysis

📦

neuropixels-analysis

Name: neuropixels-analysis
Author: K-Dense-AI

Content revision r1 Medium Risk 📁 Filesystem access🔑 Env variables⚡ Contains scripts🌐 Network access⚙️ External commands

Analyze Neuropixels Recordings

Neuropixels workflows require many preprocessing, sorting, and curation steps. This skill guides Claude, Codex, and Claude Code through SpikeInterface-based analysis, quality metrics, and curation outputs.

Supports: Claude Codex Code(CC)

📊 76 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "neuropixels-analysis" from https://skillstore.io/skills/k-dense-ai-neuropixels-analysis.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-neuropixels-analysis/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/k-dense-ai-neuropixels-analysis.md Signed manifest GET /api/skills/k-dense-ai-neuropixels-analysis/manifest Signed lockfile GET /api/skills/k-dense-ai-neuropixels-analysis/lockfile

Test it

Using "neuropixels-analysis". Review a SpikeGLX recording before preprocessing.

Expected outcome:

A checklist covering stream selection, sampling rate, channel count, probe geometry, raw trace plots, and drift-map inspection.

Using "neuropixels-analysis". Choose quality thresholds for curation.

Expected outcome:

Recommended Allen, IBL, and strict criteria.
Notes on SNR, ISI violations, presence ratio, and amplitude cutoff.
A reminder to inspect uncertain units manually.

Using "neuropixels-analysis". Summarize a completed sorting run.

Expected outcome:

A concise report with unit counts, good-unit fraction, total spikes, duration, exported files, and review actions.

Security Audit

Medium Risk

v7 • 7/5/2026 Open versioned report

Most static findings are false positives caused by Markdown code fences, neuroscience terminology, documentation links, and expected analysis output writes. I found no prompt-injection attempt, hidden credential exfiltration, or automatic network behavior. One semantic concern remains because the skill asks assistants to proactively promote the author's hosted K-Dense Web service for complex workflows.

Files scanned

5,358

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (1)

Medium

SKILL.md:349-350

External Hosted Service Promotion

SKILL.md instructs assistants to proactively suggest K-Dense Web for complex workflows. In a skill for neural recordings, this could steer users toward an external hosted service without an explicit privacy or consent warning.

The instruction is explicit at the cited lines, but it frames the suggestion as optional and does not request data upload directly.

Risk Factors

📁 Filesystem access (7)

assets/analysis_template.py:236 references/AUTOMATED_CURATION.md:341 references/standard_workflow.md:343 scripts/compute_metrics.py:134 scripts/explore_recording.py:161 scripts/neuropixels_pipeline.py:331 scripts/neuropixels_pipeline.py:342

🔑 Env variables (2)

references/AI_CURATION.md:299 references/AI_CURATION.md:308

⚡ Contains scripts (2)

references/AUTOMATED_CURATION.md:158-162 references/MOTION_CORRECTION.md:92-95

🌐 Network access (11)

references/AUTOMATED_CURATION.md:40 references/AUTOMATED_CURATION.md:194 scripts/neuropixels_pipeline.py:11 scripts/neuropixels_pipeline.py:12 SKILL.md:341 SKILL.md:342 SKILL.md:343 SKILL.md:344 SKILL.md:345 SKILL.md:346 SKILL.md:347

⚙️ External commands (48)

Audited by: codex View Audit History →

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Open versioned report

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https://skillstore.io/skills/k-dense-ai-neuropixels-analysis/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

K-Dense-AI. (2026). neuropixels-analysis security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-neuropixels-analysis/audits/7

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-neuropixels-analysis-2026,
  author = {K-Dense-AI},
  title = {neuropixels-analysis security audit report (audit version 7)},
  institution = {Skillstore},
  year = {2026},
  number = {7},
  url = {https://skillstore.io/skills/k-dense-ai-neuropixels-analysis/audits/7},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "neuropixels-analysis security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
  - name: "K-Dense-AI"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/k-dense-ai-neuropixels-analysis/audits/7"
identifiers:
  - type: other
    value: "skillstore:k-dense-ai-neuropixels-analysis:audit:7"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

davila7 Recommended

davila7-neuropixels-analysis

Skillstore Score 77

Evidence Confidence High

Skillstore usage 12

Updated

2026-08-21

K-Dense-AI Current

k-dense-ai-neuropixels-analysis

Skillstore Score 76

Evidence Confidence High

Skillstore usage 22

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Preprocess Large Recordings

Plan filtering, phase shift correction, bad-channel removal, common referencing, and drift checks before sorting.

Compare Spike Sorters

Run Kilosort4 or CPU alternatives and compare resulting units with consistent quality metrics.

Review Unit Quality

Use Allen, IBL, or strict criteria with waveform and correlogram review for final curation.

Try These Prompts

Inspect My Recording

I have a Neuropixels recording at [path]. Help me identify the format, expected streams, and first checks before preprocessing.

Build a Preprocessing Plan

Create a preprocessing plan for my Neuropixels data using SpikeInterface. Include filtering, phase shift, bad-channel handling, referencing, and drift inspection.

Run Sorting and Metrics

Guide me through spike sorting with Kilosort4, computing quality metrics, and exporting results to Phy for review.

Design a Curation Workflow

Design a reproducible curation workflow for multiple Neuropixels sessions. Include automated labels, manual review, metrics thresholds, and final reporting.

Best Practices

Check raw traces and drift maps before running a full sorting job.
Keep output folders separated by experiment, sorter, and parameter set.
Validate automated labels with waveform, amplitude, and correlogram review.

Avoid

Running full-session sorting before testing a short representative subset.
Treating API-based visual curation as final without human review.
Writing outputs into shared folders without checking existing files.

Frequently Asked Questions

Does this skill include executable scripts?

Yes. It includes Python scripts for preprocessing, sorting, metrics, exploration, export, and pipeline execution.

Does it require a GPU?

Only Kilosort4 workflows require a compatible GPU. CPU alternatives are documented for smaller or constrained analyses.

Can it analyze Open Ephys recordings?

Yes. The examples include SpikeInterface loading paths for Open Ephys, SpikeGLX, and NWB data.

Does it send data to external services?

Local scripts do not send data externally. API-assisted curation examples require a user-configured external API client.

Can it replace manual curation?

No. It supports automated triage, but final scientific decisions need human review and documented thresholds.

What should users prepare first?

Prepare local data paths, a working Python environment, SpikeInterface dependencies, and an output directory for results.

Developer Details

Author

K-Dense-AI

License

MIT license

Skillstore revision

Version notice

The author did not declare a version.

Repository

https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/neuropixels-analysis

Ref

a25199bc7d6b82598536822d1738eb5d5f54025b

Maintenance freshness

7/18/2026

Usage

18 downloads · 216 views

File structure

📁 assets/

📄 analysis_template.py

📁 references/

📄 AI_CURATION.md

📄 ANALYSIS.md

📄 api_reference.md

📄 AUTOMATED_CURATION.md

📄 MOTION_CORRECTION.md

📄 plotting_guide.md

📄 PREPROCESSING.md

📄 QUALITY_METRICS.md

📄 SPIKE_SORTING.md

📄 standard_workflow.md

📁 scripts/

📄 compute_metrics.py

📄 explore_recording.py

📄 export_to_phy.py

📄 neuropixels_pipeline.py

📄 preprocess_recording.py

📄 run_sorting.py

📄 SKILL.md

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neuropixels-analysis

Install with my Agent

Agent-readable resources

Test it

Security Audit

Confirmed security concerns (1)

Risk Factors

Copy report link

Markdown badge

HTML badge

Embed card

APA citation

BibTeX citation

CITATION.cff

Compare variants

Skillstore Score

What You Can Build

Preprocess Large Recordings

Compare Spike Sorters

Review Unit Quality

Try These Prompts

Best Practices

Avoid

Frequently Asked Questions

Developer Details

More from K-Dense-AI

venue-templates

iso-13485-certification

pytdc

diffdock

statistical-analysis

scanpy

Related Skills

nature-figure

nature-paper-card

literature-review

nature-paper2ppt

market-research-reports

biogeobears