Back to directory

Bayesian Model Update with Experimental Data

Agent skill
1 skill

Use when you have completed one or more LC-MS gradient runs, extracted separation efficiency metrics from the resulting MS1 and MS2 spectra, and need to incorporate those real experimental observations into your Gaussian process model to improve the next gradient proposal.

Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI

Supported by the Atlas install prompt. Skill-specific requirements vary.

Skill stats

Skills1CategoryScience & researchStars0

About this skill

Use when you have completed one or more LC-MS gradient runs, extracted separation efficiency metrics from the resulting MS1 and MS2 spectra, and need to incorporate those real experimental observations into your Gaussian process model to improve the next gradient proposal.

Quick start

  1. Copy the install prompt. Use the green button above this README.
  2. Send it to your agent. Paste it into your coding agent’s chat and send.
  3. Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Unavailable

HTTP 404

About scan coverage and limitations

About this listing

Category
Science & research
Reported license
Apache-2.0
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.