Variable Source Detection Skill

Compare daily photometry against baseline catalogs to detect variable and transient sources.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/dsa110/dsa110-contimg --skill variable-source-detection-skill
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Variable Source Detection Skill
Source: https://github.com/dsa110/dsa110-contimg/tree/main/backend/.github/skills/variable-source-detection
Command: npx skills add https://github.com/dsa110/dsa110-contimg --skill variable-source-detection-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the final stage of the ESE science pipeline by comparing daily photometry against baseline catalogs to identify variable sources, new transient sources, and fading sources.

Core Features & Use Cases

  • Identify Variable Sources: Detect significant flux changes from baseline, flagging potential ESE candidates.
  • Detect New Sources: Identify sources present in daily observations but absent from baseline catalogs, indicating possible transients.
  • Flag Fading Sources: Recognize baseline sources that have fallen below the detection threshold.
  • Use Case: Automatically process daily astronomical observations to flag celestial objects exhibiting unusual brightness changes, enabling rapid follow-up for transient events.

Quick Start

Use the Variable Source Detection Skill to find new and variable sources in the latest observational data against the unicat baseline catalog.

Frequently Asked Questions about Variable Source Detection Skill

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

FAQPage Schema
How do I detect transient events and new sources in daily astronomical photometry?

Detect transient events by comparing daily photometry against an established baseline catalog to identify new sources, flux variability, or fading objects. This Skill automates that comparison to flag sources appearing in daily observations but absent from the baseline.

What is ESE candidate identification and how does flux variability detection work?

ESE candidate identification detects significant flux changes from baseline levels to flag potential candidates. The mechanism works by comparing daily photometric measurements against established baseline catalogs to find sources exhibiting unusual brightness changes over time.

How do I monitor known celestial objects for fading below the detection threshold?

Monitor known celestial objects for fading by comparing baseline catalog sources against daily observations to recognize when they fall below the detection threshold. This Skill flags baseline sources that have faded from view in the latest data.

Can I use this for automated astronomical data analysis and real-time event alerting?

Yes, you can use this for automated astronomical data analysis and real-time event alerting. It processes daily observations against the baseline catalog to automatically flag variable sources, new transients, and fading objects for rapid follow-up.

Do I need a baseline catalog to identify variable sources in photometric data?

Yes, you need a baseline catalog such as the unicat reference to identify variable sources. The detection process relies on comparing daily photometry against this established baseline to accurately measure flux changes and flag anomalies.

What are the limitations of detecting variable sources without a baseline reference?

Without a baseline reference, detecting variable sources is not possible using this approach because the mechanism requires established baseline catalogs to compare daily photometry against. Accurate ESE candidate identification and transient detection depend entirely on this baseline comparison.