lp-cook

Automate LittlePea end-to-end autopilot workflows from spec to QA.

Updated Apr 14, 2026

Search Tags:#automation #workflow #orchestration #pipeline #autopilot #lp

Ready to run

npx skills add https://github.com/daudaudinang/vibecode --skill lp-cook

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: lp-cook
Source: https://github.com/daudaudinang/vibecode/tree/main/.agents/skills/lp-cook
Command: npx skills add https://github.com/daudaudinang/vibecode --skill lp-cook

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end autopilot workflows for LittlePea to execute the full pipeline from spec to QA.

Core Features & Use Cases

Orchestrates the canonical sequence: spec → plan → review → implement → review → QA, with human gates at blockers.
Supports deterministic execution, state tracking, and artifact generation for planning and delivery.
Use Case: When a feature needs end-to-end automation from requirement capture to verification, activate lp-cook to run the entire lifecycle with optional human-in-the-loop at blockers.

Quick Start

Trigger the full canonical autopilot by saying 'lp-cook, start the full spec → plan → review → implement → QA pipeline'.

Frequently Asked Questions about lp-cook

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

FAQPage Schema

How do I automate an end-to-end development pipeline from specification to QA?▼

To automate an end-to-end pipeline from specification to QA, you need a canonical orchestration workflow that directs the sequence of planning, review, implementation, and verification. This autopilot pipeline maintains state tracking and artifact generation while applying safe guardrails for deterministic execution.

What is a canonical autopilot workflow for software development?▼

A canonical autopilot workflow orchestrates the full development lifecycle sequence: spec, plan, review, implement, review, and QA. It directs this canonical sequence with deterministic execution, state tracking, and human gates at blockers to ensure safe and reliable delivery.

How do I execute a full spec to QA pipeline with human gates at blockers?▼

Executing a full spec to QA pipeline with human gates requires triggering an autopilot orchestration that directs the canonical sequence. The workflow maintains state and artifacts, pausing for human-in-the-loop review only when blockers are encountered during implementation.

Can I use deterministic execution and state tracking for feature delivery automation?▼

Yes, deterministic execution and state tracking are supported for feature delivery automation. The autopilot pipeline maintains state and generates artifacts throughout the specification, planning, review, implementation, and QA phases, enabling deterministic retries and safe guardrails.

What is the best way to orchestrate a development pipeline with safe guardrails?▼

The best way to orchestrate a development pipeline with safe guardrails is using a canonical autopilot that directs the sequence from spec to QA. It enforces safe guardrails by maintaining state, generating artifacts, and enabling deterministic retries with human gates at blockers.

Why use human-in-the-loop gates in an automated workflow pipeline?▼

Human-in-the-loop gates are used in an automated workflow pipeline to provide safe guardrails at blockers during the canonical sequence. While the autopilot handles deterministic execution from spec to QA, these human gates ensure safe intervention when the workflow encounters blockers.