fabric
Intelligent pattern selection for Fabric CLI, automatically choosing from 242+ specialized prompts for threat modeling, data analysis, summarization, and content creation.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
536 skills found
Intelligent pattern selection for Fabric CLI, automatically choosing from 242+ specialized prompts for threat modeling, data analysis, summarization, and content creation.
Build distinctive, production-grade frontend interfaces and web components with high aesthetic quality, avoiding generic AI design patterns.
Orchestrate complex multi-agent swarms with topologies like mesh, hierarchical, and star for research, development, and testing workflows.
Generate consistent, Conventional Commits-compliant messages directly from your staged git diffs.
Enhance image quality, resolution, and sharpness for screenshots and digital media. Perfect for professional documentation, blogs, and presentations.
Translates Excel (.xlsx) files from English to Chinese while preserving all formatting, images, and charts.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Self-modify your Milady agent by managing plugins. Edit code, rebuild, and restart the runtime to develop new capabilities or improve agent workflows locally.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Specialized Pest 4 agent for Laravel testing: writing, refactoring, TDD, browser/smoke tests, and architecture enforcement.
Automate the creation and maintenance of BrowserOS feature documentation using a structured, codebase-aware workflow to generate concise Mintlify MDX pages.
Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.