devorq-auto

Automate story-by-story execution of the DEVORQ v3 workflow.

13|1|Updated Apr 21, 2026

Search Tags:#automation #verification #autonomous #delegate_task #devorq #ralph-pattern #story-loop

Ready to run

npx skills add https://github.com/nandinhos/devorq_v3 --skill devorq-auto

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: devorq-auto
Source: https://github.com/nandinhos/devorq_v3/tree/main/skills/devorq-auto
Command: npx skills add https://github.com/nandinhos/devorq_v3 --skill devorq-auto

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jq, delegate_task, pint, phpunit, pytest, npm, shellcheck, python3, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Automates autonomous, story-by-story execution of the DEVORQ v3 workflow.

Core Features & Use Cases

Auto-loop: runs one story at a time using a Ralph-inspired, context-clean iteration.
Generates prd.json from SPEC.md and verifies each story with check-story gates.
Captures lessons and progress while optionally committing changes and pushing PRs.

Quick Start

Run the loop-auto script in the project root to start autonomous story-by-story execution.

Frequently Asked Questions about devorq-auto

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

FAQPage Schema

How do I automate story-by-story feature execution in my development workflow?▼

Story-by-story feature execution is automated by running a Ralph-inspired loop that processes iterative, isolated tasks with automatic context resets. The workflow generates prd.json from SPEC.md and verifies each task using check-story gates.

Do I need pytest and phpunit installed to run autonomous story verification?▼

Yes, autonomous story verification requires dependencies like pytest, phpunit, jq, pint, shellcheck, python3, and npm installed in your environment to execute the check-story gates and validation steps properly.

How does the Ralph pattern work for autonomous task delegation?▼

The Ralph pattern works by executing a continuous story-loop that processes one isolated task at a time. It uses delegate_task retry mechanisms to handle failures and performs automatic context resets between iterations to maintain clean execution state.

Can I automatically generate prd.json from SPEC.md for large feature work?▼

Yes, you can automatically generate prd.json from SPEC.md as part of the autonomous execution workflow. This conversion happens at the start of the process to define story requirements before the iterative verification gates run.

What is the best way to capture lessons and progress during autonomous story execution?▼

The best way to capture lessons and progress is through the built-in learning capture mechanism of the story-loop. It optionally commits changes and pushes PRs while recording insights gained during each isolated, iterative task execution.

When should I avoid using autonomous story-by-story automation?▼

You should avoid using autonomous story-by-story automation for small, non-iterative tasks that do not benefit from isolated context resets. It is designed specifically for large feature work requiring iterative execution and verification gates.