circadian-evolution

Name: circadian-evolution
Availability: InStock
Author: Arry8

Automate circadian self-improvement cycles for AI agents using Python and cron scheduling.

1|Updated Mar 30, 2026

Search Tags:#automation #self-improvement #training #pruning #lora #unsloth #circadian

Ready to run

npx skills add https://github.com/Arry8/openclaw-edge --skill circadian-evolution

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: circadian-evolution
Source: https://github.com/Arry8/openclaw-edge/tree/main/skills-tchif/circadian-evolution
Command: npx skills add https://github.com/Arry8/openclaw-edge --skill circadian-evolution

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires unsloth, peft, torch, and includes scripts (resource) components.

What problem does it solve?

Automates ongoing self-improvement cycles for AI agents by orchestrating a circadian loop that alternates intense daytime tasks with nightly refinement and morning reboot, reducing data noise and increasing model density.

Core Features & Use Cases

Orchestrates circadian cycle: day grind, evening analysis, night training, morning reboot for continuous improvement.
Detects data saturation, prune overfitting, and fine-tunes models using LoRA/Unsloth/pruning on daily errors with 24/7 scheduling.
Supports 24/7 operation via cron/background, with optional Colab or local GPU training for scalable experimentation.

Quick Start

Enable the circadian protocol and configure the required libraries and scheduling to start the first night training.

Frequently Asked Questions about circadian-evolution

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

FAQPage Schema

How do I automate continual self-improvement cycles for autonomous AI agents?▼

Automate continual self-improvement for AI agents by orchestrating a circadian loop that alternates daytime tasks with nightly LoRA fine-tuning on daily logs and errors, increasing model density while reducing data noise.

What is a circadian workflow for training LoRA models?▼

A circadian workflow for training LoRA models is an automated cycle featuring a day grind, evening analysis, night training, and morning reboot to continuously adapt autonomous agents from daily feedback.

Do I need a local GPU to run automated self-improvement training with Unsloth?▼

You do not strictly need a local GPU to run automated self-improvement training with Unsloth, as the cycle supports 24/7 operation via cron scheduling with optional Colab or local GPU training.

How does pruning and fine-tuning handle data saturation in autonomous agents?▼

Pruning and fine-tuning handle data saturation by detecting overfitting during the night training phase, applying LoRA and Unsloth techniques to refine the model on daily errors and reduce noise.

Can I use PEFT and Torch for scheduled background training of autonomous agents?▼

You can use PEFT and Torch for scheduled background training by configuring cron-based scheduling or background workers to execute the circadian cycle, enabling 24/7 autonomous adaptation.