trackpy-particle-tracking SKILL.md skillA

trackpy-particle-tracking from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add jaechang-hits/sciagent-skills/trackpy-particle-tracking@git:20260428.81ea2d2

Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
jaechang-hits/sciagent-skills
Path
skills/cell-biology/trackpy-particle-tracking/SKILL.md
Versions recorded
2
Latest version
git:20260428.81ea2d2, committed Apr 28, 2026
First version recorded
Feb 18, 2026
Size
27,751 bytes
Repository stars
381
License
a license file GitHub does not identify

Python library for single-particle tracking (SPT) in video microscopy via the Crocker-Grier algorithm. Locate particles (fluorescent spots, colloids, vesicles, cells) per frame, link into trajectories, filter short tracks, and compute MSD for diffusion analysis. 2D/3D with subpixel accuracy; reads TIF stacks, AVI, image series via pims. Use for quantitative SPT and diffusion coefficient extraction from fluorescence or brightfield video.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# trackpy

## Overview

trackpy is a Python library for single-particle tracking (SPT) in video microscopy. It implements the Crocker-Grier algorithm to locate bright spots in each frame with subpixel precision, then links those positions across frames into continuous trajectories. From trajectories, trackpy computes mean squared displacement (MSD), diffusion coefficients, and motion classifications (confined, normal, directed). It handles 2D fluorescence videos, 3D confocal z-stacks, and large image sequences via memory-efficient streaming through the pims image reader library.

## When to Use

- You have a fluorescence microscopy video of labeled particles (quantum dots, fluorescent beads, vesicles, receptors) and need to extract individual trajectories and diffusion coefficients.
- You want to measure particle mobility: compute MSD curves and distinguish Brownian diffusion, directed motion, or confined motion from single-particle tracks.
- You are analyzing colloid dynamics, lipid membrane diffusion, intracellular cargo transport, or virus-cell interactions where you need per-particle trajectory data.
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add jaechang-hits/sciagent-skills/trackpy-particle-tracking@sha256:80ce822cd6530eb0

The line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_q545qbd6hs4l3hdu.svg)](https://markdownregistry.com/a/art_q545qbd6hs4l3hdu)

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Versions

The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.

versioncommittedcommitsizeaudit
git:20260428.81ea2d2 latest2026-04-28 81ea2d2 27,751 BA view · diff
git:20260218.8df16942026-02-18 8df1694 27,929 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (27751 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_q545qbd6hs4l3hdu
GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/trackpy-particle-tracking
GET https://markdownregistry.com/api/v1/blob/80ce822cd6530eb0f53bb9644bd17e46c5753f4a462d06df233d49837ad29749

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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