feedback-loop

Captures human edit diffs and review comments to update software development skills and rules.

2|1|Updated Apr 7, 2026

Search Tags:#code review #software quality #continuous improvement #feedback analysis #domain adaptation

Ready to run

npx skills add https://github.com/bigeasyfreeman/adlc --skill feedback-loop-bigeasyfreeman

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: feedback-loop
Source: https://github.com/bigeasyfreeman/adlc/tree/main/skills/feedback-loop
Command: npx skills add https://github.com/bigeasyfreeman/adlc --skill feedback-loop-bigeasyfreeman

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill helps improve the efficiency and accuracy of the Build and Fix loops by learning from human edits and execution outcomes.

Core Features & Use Cases

Diff Capture: Captures and records differences between agent output and human edits.
Maintainer PR Comment Intake: Incorporates maintainer review comments as conventions.
Pattern Distillation: Identifies patterns from similar edits and distills them into rules.
Skill Update: Updates skills based on learned patterns, ensuring continuous improvement.
Domain Adaptation: Supports adaptation for different scenarios like SWElfare, Magnus, and Ratatosk.
Guardrails: Implements security and safety checks, like validation and rule effectiveness.

Quick Start

To activate the feedback-loop skill, simply use the command 'adlc run feedback-loop'.

Frequently Asked Questions about feedback-loop

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

FAQPage Schema

How do I incorporate human edits into continuous improvement for code review?▼

To incorporate human edits into continuous improvement, the system captures differences between agent output and human edits, then distills these patterns into rules to refine build and fix loops. This automates learning from code review feedback.

Can I use maintainer PR comments to update software quality rules?▼

Yes, you can use maintainer PR comments to update software quality rules. The system intakes maintainer review comments and incorporates them as conventions, ensuring that human feedback directly drives continuous improvement.

What's the best way to automate feedback analysis for build and fix loops?▼

The best way to automate feedback analysis for build and fix loops is by capturing execution outcomes and human edits, identifying patterns from similar edits, and automatically updating skills based on the distilled rules.

Does the feedback-loop process require version control for data integrity?▼

Yes, the feedback-loop process requires version control and collaboration tools. These are necessary to ensure data integrity and properly orchestrate the workflow when capturing diffs and applying learned patterns.

How do I adapt build and fix loops for different domain scenarios?▼

To adapt build and fix loops for different domain scenarios, the system supports domain adaptation for specific contexts like SWElfare, Magnus, and Ratatosk, applying learned feedback patterns to each unique environment.

What guardrails are implemented during pattern distillation from human feedback?▼

Guardrails implemented during pattern distillation include security and safety checks, specifically validation and rule effectiveness verifications. These checks ensure that learned patterns maintain software quality without compromising system integrity.