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ce-riffrec-feedback-analysis

Analyze Riffrec product feedback recordings into structured analysis reports.

Updated Jun 7, 2026
Search Tags:#analysis#bug report#product feedback#feedback analysis#Riffrec
One-click install
npx skills add https://github.com/lucking7/compound-engineering-skills --skill ce-riffrec-feedback-analysis-lucking7
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ce-riffrec-feedback-analysis
Source: https://github.com/lucking7/compound-engineering-skills/tree/main/skills/ce-riffrec-feedback-analysis
Command: npx skills add https://github.com/lucking7/compound-engineering-skills --skill ce-riffrec-feedback-analysis-lucking7

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ffmpeg, openai-api, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a streamlined workflow for analyzing product feedback captured with Riffrec, converting raw feedback into structured evidence for downstream agents.

Core Features & Use Cases

  • Feedback Analysis: Analyze product feedback from Riffrec recordings.
  • Quick Bug Report: Generate concise bug reports from short recordings.
  • Extensive Analysis: Perform in-depth analysis on longer recordings.
  • Use Case: When a user submits a Riffrec recording for product feedback, this Skill can automatically analyze the recording and provide a structured analysis report.

Quick Start

Analyze a Riffrec recording using the command: python scripts/analyze_riffrec_zip.py /path/to/input

Frequently Asked Questions about ce-riffrec-feedback-analysis

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

FAQPage Schema
How do I analyze product feedback from audio and video recordings?▼

You can analyze product feedback by running a Python script that processes the Riffrec zip file, extracting and structuring the raw audio or video data into a comprehensive analysis report for downstream processing.

Do I need ffmpeg and OpenAI API to process Riffrec feedback recordings?▼

Yes, ffmpeg and OpenAI API are required dependencies. The Skill requires ffmpeg for media processing and the OpenAI API for transcription to successfully convert raw audio or video data into structured analysis reports.

What is the best way to generate a bug report from a short screen recording?▼

The best way to generate a bug report from a short screen recording is using a feedback analysis tool that supports quick triage. This Skill processes short Riffrec recordings to automatically generate concise, structured bug reports.

How does automated feedback triage work for long user testing sessions?▼

Automated feedback triage for long user testing sessions works by processing extensive media files to identify key issues. This Skill performs in-depth analysis on longer Riffrec recordings, extracting structured evidence for downstream agents.

Can I convert raw media data into structured output for downstream processing?▼

Yes, you can convert raw media data into structured output for downstream processing. The Skill analyzes Riffrec recordings and outputs structured evidence, making the identified issues and feedback readily available for other automated agents.

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