exoplanet-workflows

Identify best-practice exoplanet detection workflows from light curves.

Updated Jan 15, 2026

Search Tags:#tls #data-quality #exoplanet #light-curves #period-search #lomb-scargle #bls

Ready to run

npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill exoplanet-workflows

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: exoplanet-workflows
Source: https://github.com/KaiserWhoLearns/skillsbench/tree/main/tasks/exoplanet-detection-period/environment/skills/exoplanet-workflows
Command: npx skills add https://github.com/KaiserWhoLearns/skillsbench --skill exoplanet-workflows

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Help researchers plan and execute exoplanet detection workflows from light curve data, reducing guesswork and enabling repeatable analyses.

Core Features & Use Cases

Guidance on selecting data loading, preprocessing, period-search, and validation steps for exoplanet pipelines.
Decision framework to choose tls, lomb-scargle, or bls based on signal type and data quality.
Troubleshooting tips for common issues like data gaps, noise, and aliasing, plus guidance for end-to-end pipeline design.

Quick Start

Plan an exoplanet detection workflow for a given light-curve dataset and suggest appropriate algorithms.

Frequently Asked Questions about exoplanet-workflows

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I choose between BLS, TLS, and Lomb-Scargle for exoplanet detection?▼

Selecting an exoplanet detection algorithm depends on your signal type and light curve data quality. A decision framework helps choose between tls, lomb-scargle, and bls to optimize detection sensitivity and minimize false positives.

What is the best way to design an end-to-end exoplanet light curve pipeline?▼

Designing an exoplanet light curve pipeline requires structured steps for data loading, preprocessing, period-search, and validation. Best-practice workflows guide pipeline architecture to ensure repeatable analyses and reduce guesswork in exoplanet detection.

How do I handle data gaps and noise when searching for exoplanet transit signals?▼

Handling data gaps and noise when searching for exoplanet transit signals requires specific troubleshooting techniques. The workflow provides guidance to address aliasing and data quality issues, improving period-search reliability across datasets.

Can I use this workflow for parameter estimation in exoplanet detection?▼

This workflow supports parameter estimation in exoplanet detection. It integrates parameter estimation workflows with data quality considerations to help researchers validate light curve analyses and refine planetary transit measurements.

When should I use Lomb-Scargle over BLS for period search in light curves?▼

Use Lomb-Scargle over BLS for period search when analyzing specific signal types within light curves. The workflow's decision framework differentiates these methods based on signal characteristics and underlying data quality.