Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
630 skills found
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.
Automated quality gate using 5 parallel AI agents to review code changes for correctness, style, and consistency.
A framework to transform experimental ML prototypes into robust, production-ready Python packages using src layout, hybrid architecture, and strict configuration management.
Refactor MoonBit code for idiomatic style: minimize public APIs, implement methods, leverage pattern matching with views, and enforce high test coverage for maintainable MoonBit projects.
Maintain and update the MassGen model registry, including backend capabilities, model metadata, pricing structures, and context window configurations for new and existing AI models.
Self-modify your Milady agent by managing plugins. Edit code, rebuild, and restart the runtime to develop new capabilities or improve agent workflows locally.
Expert-level Java codebase analysis and Maven dependency management skill. Enables deep bytecode inspection, multi-version dependency conflict resolution, and automated project building via MCP integration.
Architect multi-agent systems to overcome context limits, using patterns like supervisor, swarm, and hierarchical models to manage complex workflows.
macOS visual automation tool for precise window capture, video recording, UI mockup annotation, Excalidraw wireframing, and automated visual regression testing.
Transforms feature requests, bug reports, and improvement ideas into structured, actionable markdown project plans using repository research and industry best practices.
Transforms chat conversations into structured Notion documentation, saving insights, decisions, and knowledge to your workspace with proper organization.
Orchestrate an automated PR review-fix loop. Dispatches subagents to analyze code, CI status, and comments, then applies iterative fixes until the PR reaches a passing state.