ce-riffrec-feedback-analysis

Analyze Riffrec product feedback sessions with video, audio, and event data.

Updated Mar 29, 2026

Search Tags:#software development #analysis #bug reporting #product feedback #Riffrec

Ready to run

npx skills add https://github.com/Santiagoisper/BOPE_VERSION_DEFINITIVA --skill ce-riffrec-feedback-analysis-santiagoisper

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ce-riffrec-feedback-analysis
Source: https://github.com/Santiagoisper/BOPE_VERSION_DEFINITIVA/tree/main/.agents/skills/compound-engineering/ce-riffrec-feedback-analysis
Command: npx skills add https://github.com/Santiagoisper/BOPE_VERSION_DEFINITIVA --skill ce-riffrec-feedback-analysis-santiagoisper

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the analysis of product feedback captured with Riffrec, providing users with the ability to quickly triage and understand user feedback.

Core Features & Use Cases

Feedback Analysis: Analyze Riffrec product feedback sessions, including video, audio, and event data.
Triage Paths: Offers setup instructions, quick bug reports, and extensive analysis for deeper insights.
Use Case: A user uploads a Riffrec session containing a product feedback video. The Skill automatically analyzes the feedback and routes it to the appropriate path for further action.

Quick Start

Load the ce-riffrec-feedback-analysis skill and upload your Riffrec session.

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 Riffrec sessions?▼

To analyze product feedback from Riffrec sessions, you can load this Skill and upload your session data. It automatically processes video, audio, and event streams to provide triage and documentation.

What is the best way to triage user feedback captured with Riffrec?▼

Triageing user feedback captured with Riffrec is handled by routing session data to setup instructions, quick bug reports, or extensive analysis. This automates the categorization of captured video and audio inputs.

Do I need Python to run Riffrec feedback analysis?▼

Yes, you need Python installed to run the analysis scripts for Riffrec feedback. Additionally, an OpenAI API key is optionally required if you want to utilize media transcription for audio and video data.

Can I generate a quick bug report from Riffrec video and audio data?▼

Yes, you can generate a quick bug report from Riffrec video and audio data. The Skill evaluates the session event streams and routes the content to a quick bug reporting path for immediate documentation.

What are the limitations of using OpenAI API for Riffrec media transcription?▼

The OpenAI API is used optionally for media transcription of Riffrec sessions. Without it, the Skill cannot automatically transcribe audio and video content, limiting the depth of automated feedback analysis.

Does Riffrec feedback analysis work with event stream data?▼

Yes, Riffrec feedback analysis works directly with event stream data alongside video and audio. It processes these combined inputs to extract product feedback and route it to the appropriate analysis path.