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.
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-neuropixelsgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote 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.
[](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-neuropixels)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-neuropixels"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-neuropixels/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.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-neuropixels"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-neuropixels.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00122 | $0.03365 |
| Opus 5 | $0.00061 | $0.01682 |
| Sonnet 5 | $0.00024 | $0.00673 |
| Haiku 4.5 | $0.00012 | $0.00336 |
Grade A, and why
alterlab-neuropixels 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 12d ago.
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.
This is a copy
89% identical to neuropixels-analysis — 140 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.
How it starts
The opening of the file, as written. The whole thing — 378 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
# Bundled helper functions live in scripts/neuropixels_pipeline.py
from scripts.neuropixels_pipeline import (
load_recording, preprocess, check_drift, correct_motion,
run_spike_sorting, postprocess, curate_units, export_results, run_pipeline,
)
# 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()))
What ships with it
18 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.
- assets/analysis_template.py 8.8 KB runs code
- evals/evals.json 4.1 KB
- references/AI_CURATION.md 9.3 KB
- references/ANALYSIS.md 9.7 KB
- references/api_reference.md 9.1 KB
- references/AUTOMATED_CURATION.md 9.8 KB
- references/MOTION_CORRECTION.md 9.1 KB
- references/plotting_guide.md 11 KB
- references/PREPROCESSING.md 6.9 KB
- references/QUALITY_METRICS.md 9.2 KB
- references/SPIKE_SORTING.md 8.5 KB
- references/standard_workflow.md 9.9 KB
- scripts/compute_metrics.py 5.1 KB runs code
- scripts/explore_recording.py 5.4 KB runs code
- scripts/export_to_phy.py 2.4 KB runs code
- scripts/neuropixels_pipeline.py 13 KB runs code
- scripts/preprocess_recording.py 4.1 KB runs code
- scripts/run_sorting.py 2.5 KB runs code
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.
- 12d ago First seen · 378 lines · 122 tokens per session scan A 244271a3a19c
alterlab-neuropixels is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 8d ago), licensed MIT. It adds 122 tokens to every session and 3,365 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to neuropixels-analysis, differing in 140 lines, and is treated as a copy.
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