Where is the collected feedback stored?

Feedback can be stored inline within conversation-exit documents or aggregated in a central 'Brain Repo' for long-term tracking and analysis.

How does this skill help improve my AI agents?

It identifies patterns across multiple sessions and proposes specific changes to agent plugins, knowledge bases, or workflow templates to resolve recurring issues.

When does the Feedback Collector prompt for input?

The skill triggers automatically at the end of conversations, after significant work completion, or when it detects user frustration or manual corrections.

Can I skip the feedback process?

Yes, the skill is designed to be non-intrusive and will skip feedback requests for quick questions or when it detects the user is in a hurry.

How does the skill categorize gathered feedback?

Feedback is organized into specific categories including Usability, Accuracy, Missing Features, Documentation, Agent Behavior, Process, and Performance.

Feedback Collector

Name: Feedback Collector
Author: violetio

byvioletio

Analytics & Monitoring

Systematically gathers, categorizes, and analyzes user feedback to continuously improve AI agent performance and development workflows.

About

Feedback Collector is a specialized skill designed for Claude Code that automates the process of gathering and organizing user insights. It monitors interactions for automatic triggers like task completion or user frustration, capturing detailed feedback across categories such as usability, accuracy, and agent behavior. By identifying recurring patterns and proposing actionable improvements, this skill creates a closed-loop system that ensures your AI environment evolves based on real-world usage and specific developer needs.

Key Features

Context-aware automatic feedback triggers based on conversation milestones
Pattern recognition to identify recurring bottlenecks and friction points
Flexible storage options including inline logs and centralized brain repositories
Standardized categorization for usability, accuracy, and process issues
Actionable improvement proposals for updating plugins and knowledge bases
0 GitHub stars

Use Cases

Optimizing multi-step developer workflows by measuring interaction friction
Identifying documentation gaps based on user questions and common failures
Refining AI agent roles by tracking and resolving recurring behavioral issues

About

Key Features

Context-aware automatic feedback triggers based on conversation milestones
Pattern recognition to identify recurring bottlenecks and friction points
Flexible storage options including inline logs and centralized brain repositories
Standardized categorization for usability, accuracy, and process issues
Actionable improvement proposals for updating plugins and knowledge bases
0 GitHub stars

Use Cases

Optimizing multi-step developer workflows by measuring interaction friction
Identifying documentation gaps based on user questions and common failures
Refining AI agent roles by tracking and resolving recurring behavioral issues