clavix-summarize

Extract structured requirements from conversational data into mini-PRD, quick-PRD, and original-prompt formats.

Updated Feb 22, 2026

Search Tags:#documentation #prompt engineering #product management #requirements gathering #conversation analysis #prds

Ready to run

npx skills add https://github.com/g5becks/oxlint-plugins --skill clavix-summarize-g5becks

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clavix-summarize
Source: https://github.com/g5becks/oxlint-plugins/tree/main/.skills/clavix-summarize
Command: npx skills add https://github.com/g5becks/oxlint-plugins --skill clavix-summarize-g5becks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the challenge of capturing and structuring requirements discussed in conversations, preventing valuable insights from being lost and ensuring clear documentation for development.

Core Features & Use Cases

Requirement Extraction: Identifies and extracts key features, constraints, and objectives from conversational text.
Structured Output Generation: Creates detailed mini-PRDs, concise quick-PRDs, and raw prompt files for planning and implementation.
Use Case: After a product discovery call, use this Skill to automatically generate a mini-PRD that outlines the core features, user stories, and technical constraints discussed, ready for the development team.

Quick Start

Use the clavix-summarize skill to extract requirements from our recent conversation.

Frequently Asked Questions about clavix-summarize

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

FAQPage Schema

How do I turn conversation notes into a product requirements document?▼

You can turn conversation notes into a product requirements document by extracting structured requirements from conversational data to generate mini-PRDs, quick-PRDs, and raw prompt files. This captures key features, constraints, and objectives discussed.

What is the best way to extract requirements from a product discovery call?▼

The best way to extract requirements from a product discovery call is using conversational analysis to identify core features, user stories, and technical constraints. It validates minimum viable requirements and annotates extracted elements with confidence indicators.

Can I generate a quick-PRD from raw conversational text without writing code?▼

Yes, you can generate a quick-PRD from raw conversational text without writing code. The process focuses on requirement extraction and structured output generation, strictly adhering to mode boundaries by avoiding implementation code entirely.

How do I organize extracted product requirements after analyzing a conversation?▼

To organize extracted product requirements after analyzing a conversation, the system automatically derives project names for organized output storage. This ensures clear documentation for development and prevents valuable insights from being lost.

Does this requirement extraction approach work for validating minimum viable requirements?▼

Yes, this requirement extraction approach works for validating minimum viable requirements. It uses a defined assessment framework to ensure quality and annotates extracted elements with confidence indicators during the documentation process.