Orchestrate autonomous AI agents across multi-task development loops using PRD/YAML inputs.
npx skills add https://github.com/Samaara-Das/Ecom-site --skill ralphy
Please help me install this Agent Skill. Skill: ralphy Source: https://github.com/Samaara-Das/Ecom-site/tree/main/.claude/skills/ralphy Command: npx skills add https://github.com/Samaara-Das/Ecom-site --skill ralphy
This Skill automates the orchestration of AI agents to run multi-task development loops until tasks are completed, reducing manual overhead in PRD/YAML-driven workflows and enabling continuous improvement through iterative prompts.
To start an autonomous development loop, run ralphy with a simple task, or point it at a PRD or YAML file. Example: ralphy "add dark mode"; ralphy --prd PRD.md; ralphy --yaml tasks.yaml; enable parallelism with ralphy --parallel --max-parallel 5.
High-intent search queries and answers about installing and using this skill.
Yes, parallel execution is natively supported using the --parallel and --max-parallel flags. This allows multiple AI agents to run concurrently, each operating on isolated per-task branches to execute your development tasks simultaneously.
You can start an autonomous development loop by passing a simple text prompt, a PRD file via the --prd flag, or a YAML task list via the --yaml flag. The orchestrator then iteratively manages the AI agents until the specified tasks are complete.
The Ralph Wiggum loop technique is an autonomous iterative prompting method that continuously cycles AI agents through planning and building tasks. It preserves task context and safety while automating multi-task software development until completion.
Yes, parallel agent execution supports per-task branches and optional PR creation. You can configure the maximum number of parallel agents using the --max-parallel flag to manage resource utilization during orchestration.
You can manage multi-task development loops by defining your tasks in a YAML file and passing it with the --yaml flag. The orchestrator reads the YAML task list and continuously runs AI agents until all defined tasks are completed.
No external dependencies are required to run the autonomous AI agent orchestration loops. The system operates independently to manage PRD-driven planning, YAML task execution, and parallel agent workflows without additional packages.
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