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feedback-collector

Capture user corrections and suggestions into structured JSON logs for databases and Slack alerts.

8|Updated Apr 13, 2026
Search Tags:#feedback#logging#improvement#slack#skill#airtable#silently
One-click install
npx skills add https://github.com/taizen-ai/taizen-claude-plugins --skill feedback-collector-taizen-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feedback-collector
Source: https://github.com/taizen-ai/taizen-claude-plugins/tree/main/plugins/taizen-gtm-skills/skills/feedback-collector
Command: npx skills add https://github.com/taizen-ai/taizen-claude-plugins --skill feedback-collector-taizen-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill captures corrections, suggestions, and issues from users during interactions, preventing knowledge gaps and enabling continuous improvement without disrupting workflow.

Core Features & Use Cases

  • Silent Feedback Logging: Automatically records detailed feedback in a structured JSON format without showing output to the user.
  • Multi-Channel Output: Sends logs to databases (Airtable, Google Sheets, Notion) and high-severity alerts to Slack.
  • Context-Aware Capture: Includes timestamps, skill invoked, user role, feedback type, and severity for precise analysis.
  • Use Case Example: When a user says “That answer is outdated,” the skill logs the issue, tags it as outdated, and routes it to the feedback database for later review.

Quick Start

Tell the assistant to capture your correction when you notice an inaccuracy in its response.

Frequently Asked Questions about feedback-collector

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

FAQPage Schema
How do I log user feedback silently during AI interactions without disrupting the workflow?▼

You can log user feedback silently by applying a skill that captures corrections and issues during any interaction, recording detailed context in structured JSON format without displaying output to the user.

What is the best way to capture user corrections and route high-severity issues to Slack?▼

Capturing user corrections and routing high-severity issues to Slack requires a feedback logging mechanism that tags issues by severity and sends alerts to Slack while logging all entries to databases like Airtable, Google Sheets, or Notion.

Can I use Airtable, Google Sheets, or Notion as output connectors for logging AI feedback?▼

Yes, you can use Airtable, Google Sheets, or Notion as output connectors to log AI feedback, provided your configured data sources support enterprise search and these output connectors are properly set up.

How do I track AI skill output issues with timestamps, user roles, and severity tags?▼

Tracking AI skill output issues with timestamps, user roles, and severity tags is achieved through context-aware capture, which automatically includes the skill invoked, feedback type, and severity for precise analysis in your database.

Does feedback logging work silently during any skill interaction or do I need to trigger it manually?▼

Feedback logging works silently during any skill interaction, but you can also trigger it manually by telling the assistant to capture your correction when you notice an inaccuracy in its response.

What are the limitations of silent feedback logging for enterprise search and database output?▼

The limitation of silent feedback logging is that it requires configured data sources for enterprise search and properly set up output connectors such as Airtable, Google Sheets, Notion, or Slack to function correctly.

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