continuous-learning
[ Featured ]Continuous-learning is a skill that automatically evaluates Claude Code sessions to extract reusable patterns and saves them as learned skills for future use.
Browse and install thousands of AI Agent skills in the Killer-Skills directory. Supports Claude Code, Windsurf, Cursor, and more.
Continuous-learning is a skill that automatically evaluates Claude Code sessions to extract reusable patterns and saves them as learned skills for future use.
agent-harness-construction is a developer skill for designing and optimizing AI agent action spaces, tool definitions, and observation formatting. It focuses on core constraints like action space quality and recovery quality to achieve higher completion rates for agents like Claude.
nanoclaw-repl is a zero-dependency, session-aware REPL built on Claude for operating and extending the NanoClaw v2 AI agent. It features persistent markdown-backed sessions, dynamic skill loading, session branching, history compaction, and export capabilities to MD, JSON, and TXT formats.
agentic-engineering is an AI agent skill for engineering workflows that uses an eval-first execution loop, decomposes work into agent-sized units, and routes model tiers by task complexity to enforce quality and risk controls.
ai-first-engineering is an operating model for development teams where AI agents generate a significant portion of code implementation. It focuses on process design, review methodologies, and architecture requirements specifically optimized for AI-assisted development workflows with tools like Claude Code.
A comprehensive verification system for Claude Code sessions.
Scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions.
C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
Translate visa application documents (images) to English and create a bilingual PDF with original and translation
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.