Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
149 skills found
Nonlinear optimization toolkit using CasADi and IPOPT. Ideal for building complex NLP models, defining symbolic variables, constraints, and solvers, with specialized support for power systems optimization patterns.
Queen-led multi-agent orchestration for Claude Code, featuring Byzantine consensus, persistent collective memory, and adaptive task distribution for complex software projects.
Persistent, Git-friendly memory for Claude. Automatically store and retrieve project decisions, bug fixes, and coding patterns in a local .mv2 file.
A wise conductor of expert agents. It helps you achieve goals by summoning, orchestrating, and creating specialized AI experts. Features intellectual humility, multi-agent debate, and self-learning pattern capture.
Self-modify your Milady agent by managing plugins. Edit code, rebuild, and restart the runtime to develop new capabilities or improve agent workflows locally.
Production-ready reinforcement learning using Stable Baselines3. Train agents, design custom environments, implement training callbacks, and optimize workflows with a scikit-learn-style API.
Process and generate multimedia with Google Gemini. Analyze audio, images, videos, and PDFs with high-context windows. Supports transcription, visual QA, OCR, and AI-driven image creation.
Coverage-guided fuzzer for Ruby code and C extensions, powered by libFuzzer and address sanitizers to detect memory corruption and undefined behavior.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Log ideas, notes, and learning progress chronologically to project archives using a CLI helper tool for systematic knowledge retention.
Manage automatic model routing for Higress AI Gateway via CLI. Configure triggers for intelligent model selection based on request content.
Comprehensive toolkit for graph creation, network analysis, and visualization in Python. Ideal for analyzing relationships, centrality, community detection, and synthetic network generation across diverse research domains.