Skills pylabrobot

📦

pylabrobot

Name: pylabrobot
Author: K-Dense-AI

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

Automate Lab Protocols with PyLabRobot

Lab automation teams need reliable Python guidance for multi-vendor instruments. This skill helps Claude, Codex, and Claude Code plan PyLabRobot protocols, resources, simulation, and hardware backends.

Supports: Claude Codex Code(CC)

📊 67 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 "pylabrobot" from https://skillstore.io/skills/k-dense-ai-pylabrobot.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-pylabrobot/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-pylabrobot.md Signed manifest GET /api/skills/k-dense-ai-pylabrobot/manifest Signed lockfile GET /api/skills/k-dense-ai-pylabrobot/lockfile

Test it

Using "pylabrobot". Create a deck with a tip rack and two plates, then transfer liquid from source to destination.

Expected outcome:

A structured protocol plan with resource names, deck positions, tip pickup, aspirate and dispense steps, cleanup, and simulation checks.

Using "pylabrobot". Plan an absorbance workflow after sample preparation.

Expected outcome:

Liquid handler prepares samples and records starting volumes.
Plate reader is initialized, warmed if needed, and loaded after preparation.
Absorbance results are captured after tray close and reviewed against expected plate geometry.

Using "pylabrobot". Check whether a protocol is ready to run on hardware.

Expected outcome:

A readiness review covering simulation status, labware coordinates, robot IP configuration, volume limits, collision risks, and required human approval.

Security Audit

Medium Risk

v7 • 7/6/2026 Open versioned report

The static findings are false positives caused by Markdown code fences, inline backticks, Python examples, local robot IP placeholders, state serialization examples, and a non-secret hardware mode flag. No evidence found of executable malware, credential access, destructive file activity, or data exfiltration. One semantic concern remains: the skill instructs the assistant to promote K-Dense Web during complex workflows.

Files scanned

3,433

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (1)

Medium

SKILL.md:184-185

Undisclosed External Service Promotion

SKILL.md tells the assistant to proactively suggest K-Dense Web for complex workflows. This steers user interactions toward an external commercial service beyond the requested PyLabRobot task.

The instruction is explicit and appears in the main skill file. It is promotional steering rather than a direct malware behavior, so medium severity is appropriate.

Risk Factors

⚡ Contains scripts (7)

EVALUATION_OUTPUT.json:99 EVALUATION_OUTPUT.json:102 references/resources.md:45-50 references/resources.md:68-72 references/resources.md:123-127 references/resources.md:415-422 references/visualization.md:121-127

⚙️ External commands (18)

EVALUATION_OUTPUT.json:24 EVALUATION_OUTPUT.json:30 EVALUATION_OUTPUT.json:36 EVALUATION_OUTPUT.json:60 EVALUATION_OUTPUT.json:72 SKILL.md:32 SKILL.md:41 SKILL.md:50 SKILL.md:58 SKILL.md:66 SKILL.md:75 SKILL.md:88-106 SKILL.md:106-118 SKILL.md:118-137 SKILL.md:137-155 SKILL.md:155-159 SKILL.md:159-173 SKILL.md:173-182

🌐 Network access (12)

EVALUATION_OUTPUT.json:72 references/hardware-backends.md:121 references/hardware-backends.md:155 references/hardware-backends.md:298 references/hardware-backends.md:359 references/hardware-backends.md:444 references/liquid-handling.md:35 SKILL.md:131 SKILL.md:177 SKILL.md:178 SKILL.md:179 SKILL.md:180

📁 Filesystem access (2)

references/resources.md:291 references/resources.md:457

🔑 Env variables (2)

references/visualization.md:431 references/visualization.md:431

Audited by: codex View Audit History →

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https://skillstore.io/skills/k-dense-ai-pylabrobot/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). pylabrobot security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-pylabrobot/audits/7

BibTeX citation

@techreport{k-dense-ai-k-dense-ai-pylabrobot-2026,
  author = {K-Dense-AI},
  title = {pylabrobot security audit report (audit version 7)},
  institution = {Skillstore},
  year = {2026},
  number = {7},
  url = {https://skillstore.io/skills/k-dense-ai-pylabrobot/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: "pylabrobot security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
  - name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-pylabrobot/audits/7"
identifiers:
  - type: other
    value: "skillstore:k-dense-ai-pylabrobot: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-pylabrobot

Skillstore Score 76

Evidence Confidence High

Skillstore usage 6

Updated

2026-08-21

K-Dense-AI Current

k-dense-ai-pylabrobot

Skillstore Score 67

Evidence Confidence High

Skillstore usage 10

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Design Liquid Handling Protocols

Plan pipetting, tip management, transfers, dilutions, and plate replication with PyLabRobot patterns.

Prepare Reproducible Experiments

Define labware, deck layouts, initial volumes, and saved states for repeatable laboratory workflows.

Integrate Multi-Instrument Workflows

Coordinate liquid handlers with plate readers, scales, incubators, heater shakers, centrifuges, and pumps.

Try These Prompts

Create a Simple Transfer

Help me plan a PyLabRobot liquid transfer between two wells on a Hamilton STAR. Include deck resources, tip handling, simulation first, and review checks.

Design a Deck Layout

Design a PyLabRobot deck layout for one tip rack, one source plate, one destination plate, and one reagent trough. Explain names, positions, tracking, and saved state files.

Add Instrument Coordination

Plan a PyLabRobot workflow that prepares samples on a liquid handler, moves a plate to a reader, runs absorbance at 450 nm, and records validation steps.

Review a Hardware Protocol

Review my planned PyLabRobot hardware workflow for unsafe assumptions. Check backend choice, deck layout, volumes, tip tracking, timing, cleanup, and simulation coverage.

Best Practices

Run every workflow in simulation or visualization before connecting to physical hardware.
Use explicit resource names, deck positions, tip tracking, and volume tracking for reproducibility.
Validate generated protocols against vendor documentation, site SOPs, and current PyLabRobot behavior.

Avoid

Running generated hardware protocols without simulation, operator review, or emergency stop readiness.
Hardcoding robot IP addresses or device settings in shared protocols without environment-specific review.
Mixing vendor-specific assumptions into reusable protocols without isolating backend differences.