What is the Ralph loop referenced in this skill?

The Ralph loop is an autonomous development workflow that utilizes structured JSON data to track, manage, and execute technical tasks derived from project requirements.

Why does this skill use a hybrid approach for conversion?

Python scripts provide fast, deterministic parsing of Markdown patterns, while AI validation identifies subtle nuances, recomputes hashes, and ensures logical consistency that scripts might miss.

How are story dependencies handled?

The skill identifies specific syntax, such as '(depends: STORY-XXX)', within the PRD to build a dependency graph, ensuring tasks are executed in the correct logical order.

Can I use this without the Ralph framework?

While optimized for the Ralph workflow, the resulting prd.json file follows a standard schema that can be adapted for other autonomous agents or custom task tracking systems.

What is the purpose of the content_hash field?

The content_hash is a 64-character hex string generated from task details to detect if a requirement has been modified, allowing the system to determine if a task needs to be re-executed.

PRD to JSON Task Generator

Name: PRD to JSON Task Generator
Author: qte77

byqte77

0•

생산성 및 워크플로

Converts Markdown requirements documents into structured JSON task tracking files for autonomous development workflows.

This skill automates the transition from high-level product requirements to actionable, machine-readable tasks by converting PRD.md files into a structured prd.json format. Utilizing a hybrid approach of Python-based parsing and AI-driven validation, it ensures that every feature is accurately identified, cross-referenced, and assigned unique identifiers, acceptance criteria, and dependency mappings. It is an essential utility for teams using the Ralph workflow to initialize autonomous execution loops with high precision, maintaining strict data integrity between documentation and code execution.

주요 기능

010 GitHub stars

02Hybrid parsing using Python scripts combined with AI validation for maximum accuracy.

03Dry-run capability to identify and resolve parsing issues before writing files.

04Automatic extraction of story dependencies, acceptance criteria, and target file paths.

05Integrated content hashing to detect requirement changes and preserve state.

06Comprehensive validation checklist ensuring schema compliance and logical integrity.

사용 사례

01Automating the creation of structured, machine-readable backlogs from unstructured text.

02Synchronizing technical task tracking with updated product documentation.

03Initializing autonomous development loops from static Markdown requirements.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qte77/claude-code-utils-plugin generating-prd-json-from-prd-md

For use in Claude.ai and ChatGPT

주요 기능

010 GitHub stars

02Hybrid parsing using Python scripts combined with AI validation for maximum accuracy.

03Dry-run capability to identify and resolve parsing issues before writing files.

04Automatic extraction of story dependencies, acceptance criteria, and target file paths.

05Integrated content hashing to detect requirement changes and preserve state.

06Comprehensive validation checklist ensuring schema compliance and logical integrity.

사용 사례

01Automating the creation of structured, machine-readable backlogs from unstructured text.

02Synchronizing technical task tracking with updated product documentation.

03Initializing autonomous development loops from static Markdown requirements.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qte77/claude-code-utils-plugin generating-prd-json-from-prd-md

For use in Claude.ai and ChatGPT