AI Agent Skills Marketplace

Published AI benchmarks measure brains in jars. They test models in isolation or within a single reference harness — and then attribute all performance to the model. This skill teaches you to decompose agent performance into its two actual components: model capability and harness multiplier. The result is evaluations that predict real-world behavior instead of benchmark theater.

Professional prompt engineering patterns for building robust, secure, and production-ready LLM applications.

Evaluates AI coding agent platforms across five structural dimensions that determine real-world performance independently of model quality, so teams select on architectural fit rather than benchmark scores.

Professional prompt engineering, audit, and evaluation system for production-grade AI agents and workflows.

Design, debug, and harden AI control loops with explicit contracts and automated verification harnesses.