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.