harness

Automates the build-test-grade loop for full-stack application MVPs.

2|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/hamzaPixl/pixl-ai --skill harness-hamzapixl
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: harness
Source: https://github.com/hamzaPixl/pixl-ai/tree/main/packages/crew/skills/harness
Command: npx skills add https://github.com/hamzaPixl/pixl-ai --skill harness-hamzapixl

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The harness skill automates the end‑to‑end creation of full‑stack applications, providing a structured generate‑evaluate‑iterate loop that ensures high‑quality, production‑ready MVPs without manual coding cycles.

Core Features & Use Cases

  • Planner agent creates a detailed specification from a concise product description.
  • Generator agent builds the application code and validates basic functionality.
  • Dual evaluator agents score the app on design, originality, craft, and functionality using Playwright tests.
  • Consensus scoring and escalation enforce integrity, budget limits, and prevent stagnation.
  • Use case: Rapidly prototype a task‑management tool, e‑commerce site, or internal dashboard with AI‑driven quality assurance.

Quick Start

Create a task management app with kanban boards and AI prioritization using the harness skill.

Frequently Asked Questions about harness

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

FAQPage Schema
How do I automate full-stack application generation and quality evaluation?

Automate full-stack application generation using a structured generate-evaluate-iterate loop that builds code, runs Playwright tests, and grades design, originality, craft, and functionality to produce high-quality MVPs.

What is an AI-driven generate-evaluate-iterate loop for app prototyping?

An AI-driven generate-evaluate-iterate loop for app prototyping is a workflow where a planner creates specs, a generator builds code, and dual evaluators score quality using Playwright tests to refine full-stack MVPs autonomously.

Can I use Playwright tests to evaluate generated MVP code automatically?

Yes, you can use Playwright tests to evaluate generated MVP code automatically by running dual evaluator agents that grade applications across design, originality, craft, and functionality.

How do I prevent stagnation when iterating on AI-generated applications?

Prevent stagnation when iterating on AI-generated applications by using consensus scoring and escalation mechanisms that enforce integrity, apply anti-rationalization checks, and maintain strict budget constraints.

Does autonomous app generation work for rapid prototyping of internal dashboards?

Autonomous app generation works for rapid prototyping of internal dashboards by taking a concise product description and coordinating planner, generator, and evaluator agents to output a production-ready MVP.

What are the limitations of using autonomous generation loops for full-stack apps?

Limitations of autonomous generation loops include strict budget constraints and enforced integrity rules that may halt iteration if consensus scoring detects stagnation or anti-rationalization thresholds are triggered.