Agent Skills Hub

semantic-compression

Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.

agno

Framework for building multi-agent systems, AgentOS runtimes, and MCP-integrated AI agents.

markdown-token-optimizer

Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.

mystery-novel-conventions

A framework for crafting suspense, detective, and mystery narratives, emphasizing fair play principles, clue placement, and plot structure.

context-optimization

Optimize agent context windows through KV-caching, observation masking, summarization-based compaction, and context partitioning to reduce costs and latency.

skill-customizer

Adapt existing skills to your unique workflow, or create new ones for repetitive, time-consuming tasks.

tool-integration

Create, register, and manage custom agent tools and MCP servers to extend AI agent capabilities with external APIs and custom logic.

language-learning

AI language tutor for personalized learning through conversation, grammar lessons, vocabulary drills, and flashcards. Supports 100+ languages including Spanish, French, Japanese, and Mandarin.

worker-integration

Intelligent orchestration for dispatching tasks to specialized background agents with performance-based routing and execution tracking.

juliaz-tool-builder

Expert guidance for designing and implementing high-quality tool schemas and descriptions for Julia's agent systems, ensuring reliable tool execution and reducing model hallucinations.

research-review

Get deep, critical, NeurIPS/ICML-style peer reviews of your research, paper drafts, and experimental setups using external LLMs via Codex MCP.

refactor

A specialized skill for surgical code refactoring. Improves maintainability, reduces technical debt, and applies design patterns without altering external behavior.