AI-powered prompt optimization hook for Claude Code. Transforms simple prompts into comprehensive, structured instructions using Claude Opus 4.6's advanced reasoning capabilities.

Loop until it's better — drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts.

Collection of Claude Skills for DSPy framework - program language models, optimize prompts, and build RAG pipelines systematically

Claude Code skill that forces AI to understand before executing. Three disciplines: cognition check, requirement understanding, method search.

Optimize any AI agent’s skills, tools/MCP, and prompts against your own evals.

Skills that translate your coding agent's output into plain language: honest reports, straight verdicts, steps you can follow. MIT.

Turn Claude Code into its own Meta-Harness — a skill that evolves the scaffolding around a fixed model (memory, retrieval, context, prompts) via a native propose→score→Pareto loop. Native reimplementation of Meta-Harness (Lee et al. 2026).

A CLI tool for logging and analyzing Claude Code and Cursor ai-driven coding session.

Agent skill for analyzing and improving prompts using 31 frameworks across 7 intent categories. Works with Claude Code, Gemini CLI, Cursor, Copilot, and 30+ Agent Skills compatible tools.