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iJosueeh
iJosueehCOMMUNITY
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feedback-writer

Captures and classifies user feedback with scoring metrics for AI skill execution.

Updated Apr 3, 2026
Search Tags:#continuous improvement#user feedback#ai feedback#performance assessment#ai system quality
One-click install
npx skills add https://github.com/iJosueeh/nexora-web --skill feedback-writer-ijosueeh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feedback-writer
Source: https://github.com/iJosueeh/nexora-web/tree/main/.opencode/skills/feedback-writer
Command: npx skills add https://github.com/iJosueeh/nexora-web --skill feedback-writer-ijosueeh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires feedback-observer, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a systematic way to capture, categorize, and record user feedback and performance assessments of AI skill executions, improving the overall quality and reliability of AI systems.

Core Features & Use Cases

  • Feedback Capture: Record user corrections, improvements, and assessments during skill execution.
  • Automated Classification: Classify feedback into skill defects, execution lapses, or unclear cases based on context.
  • Quality Scoring: Provide structured feedback entries with scores for Precision, Coverage, Efficiency, and Satisfaction.
  • Integration with Feedback Observer: Automatically triggers feedback recording upon AI execution or manual commands.
  • Use Case: Enhance AI capabilities by leveraging user feedback for continuous improvement.

Quick Start

Enable the feedback-writer skill within your AI platform or tool.

Frequently Asked Questions about feedback-writer

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

FAQPage Schema
How do I capture and categorize user feedback during AI skill execution?▼

You can capture user feedback during AI skill execution by using automated classification to sort entries into skill defects, execution lapses, or unclear cases based on context. This process records corrections and assessments systematically to improve system reliability.

What is the best way to score AI system quality using user feedback?▼

Scoring AI system quality requires structuring feedback entries with metrics for Precision, Coverage, Efficiency, and Satisfaction. This provides a quantitative assessment of AI skill performance alongside qualitative user corrections.

Do I need feedback-observer to record AI performance assessments?▼

Yes, feedback-observer is a required prerequisite skill. The feedback-writer skill integrates with feedback-observer systems to automatically trigger feedback recording upon AI execution or manual commands.

Can I use Python to automate feedback capture and processing for AI systems?▼

Yes, you can use Python and structured data formats to automate feedback capture and streamline processing. This setup allows for systematic recording and categorization of user corrections during skill execution.

When do I need structured data formats for continuous improvement of AI skills?▼

You need structured data formats for continuous improvement when you want to systematically categorize user feedback and performance assessments. This enables automated classification into defects or lapses, supporting reliable AI system quality enhancements.

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