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feedback-capture

Detect user corrections and learning feedback within ask-question sessions.

1|Updated May 15, 2026
Search Tags:#intelligent assistance#feedback detection#user learning#inline correction#AI question skills
One-click install
npx skills add https://github.com/Amar1404/AI_ANALYST --skill feedback-capture-amar1404
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feedback-capture
Source: https://github.com/Amar1404/AI_ANALYST/tree/main/skills/feedback-capture
Command: npx skills add https://github.com/Amar1404/AI_ANALYST --skill feedback-capture-amar1404

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Detects and learns from corrections and learnings embedded within user messages. Reduces manual analysis by incorporating this feature within question skills.

Core Features & Use Cases

  • Automated Feedback Detection: Identifies user corrections and learnings inline while interacting with the AI question skills.
  • Seamless Integration: This functionality is embedded within the ask-question skill and operates without the need for separate invocation.
  • Use Case: When using the ask-question skill, automatically recognize and analyze any feedback or additional learning points provided by users without explicit command input.

Quick Start

Simply engage with the ask-question skill as usual; no need for specific feedback detection commands.

Frequently Asked Questions about feedback-capture

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

FAQPage Schema
How does inline feedback detection work in AI question skills?▼

Inline feedback detection works by automatically identifying user corrections and learnings embedded within messages during real-time interactive sessions, without requiring separate commands.

Do I need to invoke a specific command to capture user corrections during an interactive session?▼

No, you do not need specific commands. User corrections are captured seamlessly within the ask-question skill, operating automatically during real-time interactions without explicit invocation.

What is the best way to automate user learning detection in real-time interactions?▼

Automated user learning detection is best handled by embedding feedback capture directly within interactive question skills, recognizing corrections inline to reduce manual analysis.

Can I use this automated feedback detection outside of the ask-question skill?▼

No, this automated feedback detection is built-in specifically for the ask-question skill. It applies to real-time interactive sessions within that context to handle user corrections.

Why should I use built-in feedback capture instead of manual analysis for user corrections?▼

Built-in feedback capture reduces manual analysis by automatically detecting and learning from corrections embedded in user messages, streamlining real-time interactive sessions without extra input.

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