设计与多媒体

gan-style-harness

affaan-m/ecc

GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper. Use when a feature should be built autonomously through generator and evaluator iteration until it clears a quality bar.

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安装命令

npx skills add https://github.com/affaan-m/ecc --skill gan-style-harness

SKILL.md

GAN-Style Harness Skill

Inspired by Anthropic's Harness Design for Long-Running Application Development (March 24, 2026)

A multi-agent harness that separates generation from evaluation, creating an adversarial feedback loop that drives quality far beyond what a single agent can achieve.

Core Insight

When asked to evaluate their own work, agents are pathological optimists — they praise mediocre output and talk themselves out of legitimate issues. But engineering a separate evaluator to be ruthlessly strict is far more tractable than teaching a generator to self-critique.

This is the same dynamic as GANs (Generative Adversarial Networks): the Generator produces, the Evaluator critiques, and that feedback drives the next iteration.

When to Use

  • Building complete applications from a one-line prompt
  • Frontend design tasks requiring high visual quality
  • Full-stack projects that need working features, not just code
  • Any task where "AI slop" aesthetics are unacceptable
  • Projects where you want to invest $50-200 for production-quality output

GAN-Style Harness Skill

Inspired by Anthropic's Harness Design for Long-Running Application Development (March 24, 2026)

A multi-agent harness that separates generation from evaluation, creating an adversarial feedback loop that drives quality far beyond what a single agent can achieve.

Core Insight

When asked to evaluate their own work, agents are pathological optimists — they praise mediocre output and talk themselves out of legitimate issues. But engineering a separate evaluator to be ruthlessly strict is far more tractable than teaching a generator to self-critique.

This is the same dynamic as GANs (Generative Adversarial Networks): the Generator produces, the Evaluator critiques, and that feedback drives the next iteration.

When to Use

  • Building complete applications from a one-line prompt
  • Frontend design tasks requiring high visual quality
  • Full-stack projects that need working features, not just code
  • Any task where "AI slop" aesthetics are unacceptable
  • Projects where you want to invest $50-200 for production-quality output