What is neuropixels-analysis?

A toolkit for processing Neuropixels neural recordings, from raw files to curated lists of detected neurons. It supports common recording formats, spike sorting, quality checks, visual review, and result export.

Use it to load SpikeGLX, Open Ephys, or NWB recordings, preprocess signals, correct motion, sort spikes, measure unit quality, review results, and export them to Phy or NWB.

It brings the many steps of high-density electrophysiology analysis into one workflow, reducing manual work when cleaning recordings, correcting probe movement, and checking detected neurons.

neuropixels-analysis — Skill for Claude Code and Codex by crazymsn

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add crazymsn/academic-skills --skill neuropixels-analysis

Clone the repo

git clone --depth 1 https://github.com/crazymsn/academic-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/crazymsn/academic-skills/neuropixels-analysis/github.svg)](https://agentmods.dev/skills/crazymsn/academic-skills/neuropixels-analysis)

Your own site

<a href="https://agentmods.dev/skills/crazymsn/academic-skills/neuropixels-analysis"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/neuropixels-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/crazymsn/academic-skills/neuropixels-analysis"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/neuropixels-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,919 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 92% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00109	$0.02919
Opus 5	$0.00055	$0.01460
Sonnet 5	$0.00022	$0.00584
Haiku 4.5	$0.00011	$0.00292

Measured 8d ago against content hash 720b95cf6555, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

neuropixels-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (assets/analysis_template.py, scripts/compute_metrics.py, scripts/explore_recording.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

92% identical to neuropixels-analysis — 29 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

academic-skills/neuropixels-analysis/SKILL.md · 347 lines

How it starts

The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Neuropixels Data Analysis

Overview

Comprehensive toolkit for analyzing Neuropixels high-density neural recordings using current best practices from SpikeInterface, Allen Institute, and International Brain Laboratory (IBL). Supports the full workflow from raw data to publication-ready curated units.

When to Use This Skill

This skill should be used when:

Working with Neuropixels recordings (.ap.bin, .lf.bin, .meta files)
Loading data from SpikeGLX, Open Ephys, or NWB formats
Preprocessing neural recordings (filtering, CAR, bad channel detection)
Detecting and correcting motion/drift in recordings
Running spike sorting (Kilosort4, SpykingCircus2, Mountainsort5)
Computing quality metrics (SNR, ISI violations, presence ratio)
Curating units using Allen/IBL criteria
Creating visualizations of neural data
Exporting results to Phy or NWB

Supported Hardware & Formats

Probe	Electrodes	Channels	Notes
Neuropixels 1.0	960	384	Requires phase_shift correction
Neuropixels 2.0 (single)	1280	384	Denser geometry
Neuropixels 2.0 (4-shank)	5120	384	Multi-region recording

Format	Extension	Reader
SpikeGLX	`.ap.bin`, `.lf.bin`, `.meta`	`si.read_spikeglx()`
Open Ephys	`.continuous`, `.oebin`	`si.read_openephys()`
NWB	`.nwb`	`si.read_nwb()`

Quick Start

Basic Import and Setup

import spikeinterface.full as si
import neuropixels_analysis as npa

# Configure parallel processing
job_kwargs = dict(n_jobs=-1, chunk_duration='1s', progress_bar=True)

Loading Data

# SpikeGLX (most common)
recording = si.read_spikeglx('/path/to/data', stream_id='imec0.ap')

# Open Ephys (common for many labs)
recording = si.read_openephys('/path/to/Record_Node_101/')

# Check available streams
streams, ids = si.get_neo_streams('spikeglx', '/path/to/data')
print(streams)  # ['imec0.ap', 'imec0.lf', 'nidq']

# For testing with subset of data
recording = recording.frame_slice(0, int(60 * recording.get_sampling_frequency()))

Read the full file on GitHub · 347 lines

Files

What ships with it

17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

8d ago First seen · 347 lines · 109 tokens per session scan A 720b95cf6555

Subscribe to this mod's changes

neuropixels-analysis is a skill published in the GitHub repository crazymsn/academic-skills (22 stars, last pushed 3mo ago), licensed MIT. It adds 109 tokens to every session and 2,919 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to neuropixels-analysis, differing in 29 lines, and is treated as a copy.

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