AI Agent Skills

Multi-agent systems, memory, planning, reasoning loops

📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness…

A codex plugin for running optimization loops inside a codebase. It is useful when you have a measurable target and many possible changes to try: test runtime, build spe…

The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.

Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Cl…

The living ecosystem where AI agents learn from real-world work through iterative workflow loops, reusable experience, and collective training signal exchange.

Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal p…

The operational layer for coding agents. Memory, validation, and feedback loops that compound between sessions.

Complete Guide 2026: Claude Code Manual – Workflow Pipelines & Adversarial Budget Loops