mcp-gateway-patterns
MCP Gateway design patterns for managing Agent Gateway, Subprocess, and Daemon isolation strategies to optimize context token usage and system performance.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
625 skills found
MCP Gateway design patterns for managing Agent Gateway, Subprocess, and Daemon isolation strategies to optimize context token usage and system performance.
LinkedIn automation and integration for managing profiles, connections, posts, and organizations using the Membrane CLI.
Standardized React UI patterns for loading states, error handling, and data fetching to ensure consistent UX and robust component architecture.
Manage Jenkins CI/CD pipelines via REST API. Trigger builds, monitor job status, view console logs, and manage nodes and queues directly from your terminal or AI agent.
A nested plugin architecture for Claude Code that optimizes context by dynamically loading playbooks, skills, and agents to save over 90% in token usage.
Self-modify your Milady agent by managing plugins. Edit code, rebuild, and restart the runtime to develop new capabilities or improve agent workflows locally.
Robot perception system design, configuration, and optimization for cameras, LiDAR, and sensor fusion pipelines. Includes camera calibration, 3D reconstruction, and production deployment best practices.
Development guide for self-improving MassGen via programmatic automation testing and visual UI/UX evaluation.
A framework for managing the end-to-end LLM project lifecycle, from evaluating task-model fit and pipeline architecture design to implementing structured output parsing and agent-assisted development.
Analyze and audit React projects for security, performance, correctness, and architecture issues with actionable diagnostics and scoring.
A configuration and usage guide for the XRequest tool within the Ant Design X SDK, streamlining network integration for streaming AI interfaces.
Behavioral guidelines for LLMs to reduce coding mistakes, follow best practices, and improve output quality by enforcing simplicity, surgical changes, and goal-driven verification.