cellprofiler SKILL.md skillA

cellprofiler from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add k-dense-ai/scientific-agent-skills/cellprofiler@v1.1

Pins v1.1 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
k-dense-ai/scientific-agent-skills
Path
skills/cellprofiler/SKILL.md
Versions recorded
2
Latest version
v1.1, committed Oct 1, 2026
First version recorded
Sep 30, 2026
Size
7,707 bytes
Repository stars
56,497
License
MIT

Runs reproducible CellProfiler microscopy pipelines for nuclear segmentation, cell counts, and per-object fluorescence measurements. Supports image/channel manifests, headless batch execution, segmentation overlays, and measurement QC for 2D fluorescence assays.

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

# CellProfiler quantitative microscopy

Use this skill when a user needs a repeatable CellProfiler `.cppipe`, nuclear counts, nuclear
fluorescence, or batch microscopy measurements. The bundled assay accepts **one 2D grayscale
TIFF nuclear channel per field**, with black-is-zero (MINISBLACK) pixels and bright nuclei on a
dark background. Palette and white-is-zero TIFFs need an explicit conversion. For volumetric
segmentation, multichannel cell painting, or tissue-specific models, design a separate pipeline
and validate those assumptions rather than silently projecting or splitting the images.

The official application and manual remain **4.2.8**. PyPI publishes **4.2.8.1**; its seven
modules used here and embedded Threshold module match the 4.2.8 source, but this review did
not execute that native distribution. Keep the helper environment separate from CellProfiler's
older dependency stack; see the runtime reference for the verification boundary.

## Workflow

1. Establish the acquisition unit: plate, well, site, time point if present, pixel size, nuclear
   channel identity, camera bit depth, exposure, and biological replicate. Keep original image
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add k-dense-ai/scientific-agent-skills/cellprofiler@sha256:b822ed64acb189d9

The line at the top of this page pins the label v1.1, 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_gul76gibweaohlbp.svg)](https://markdownregistry.com/a/art_gul76gibweaohlbp)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 2 versions of this file, between Sep 30, 2026 and Oct 1, 2026, more than one a day.

versioncommittedcommitsizeaudit
v1.1 latest2026-10-01 a92663a 7,707 BA view · diff
v1.02026-09-30 9c044a1 5,556 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 (7707 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

k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_gul76gibweaohlbp
GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/cellprofiler
GET https://markdownregistry.com/api/v1/blob/b822ed64acb189d900f59ba69418e5e41261d539fd2fd847e402cded2fc1bb38

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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