learning-loop

Detect complex task sequences and suggest reusable skill creation in Microclaw.

Updated May 5, 2026

Search Tags:#skill creation #task automation #microclaw #skill tracking #task detection

Ready to run

npx skills add https://github.com/saif27217/microclaw-setup --skill learning-loop-saif27217

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: learning-loop
Source: https://github.com/saif27217/microclaw-setup/tree/main/skills/learning-loop
Command: npx skills add https://github.com/saif27217/microclaw-setup --skill learning-loop-saif27217

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The learning-loop skill solves the problem of manually creating and managing reusable skills by automatically detecting complex tasks and suggesting their automation.

Core Features & Use Cases

Task Detection: Automatically identifies tasks with high complexity and potential for reuse.
Skill Proposal: Offers to create a reusable skill from detected tasks, capturing detailed steps and outcomes.
Skill Tracking: Monitors skill usage and success rates for continuous improvement.
Integration: Works alongside continuous-learning-v2 to evolve skills from instincts and observations.

Quick Start

After completing a complex task, say "Create skill from this task" to automatically generate and save a skill for future use.

Frequently Asked Questions about learning-loop

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

FAQPage Schema

How do I automate skill creation from complex task sequences?▼

To automate skill creation from complex task sequences, you can trigger the detection mechanism by saying "Create skill from this task" after completing a multi-step workflow, which captures the detailed steps and outcomes to generate a reusable skill.

What is task detection for reusable skill creation?▼

Task detection for reusable skill creation is an automated process that identifies multi-step workflows with high complexity and reuse potential, then suggests converting those completed task sequences into structured skills within the Microclaw framework.

Does skill tracking monitor the success rates of automated tasks?▼

Yes, skill tracking monitors the usage and success rates of automated tasks to ensure continuous improvement, allowing you to perform periodic reviews for optimizing your created skills.

Can I use this to evolve skills from instincts and observations?▼

You can evolve skills from instincts and observations by integrating this with the continuous-learning-v2 framework, which works alongside task detection to refine and automate complex multi-step workflows.

What are the limitations of automatically detecting complex tasks?▼

The limitation of automatically detecting complex tasks is that it requires task completion with multi-step workflows and clear potential for reuse, meaning single-step or non-repetitive processes will not trigger skill creation proposals.