Topic: mcp
13,395 skills in this topic.
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langgraph
LangGraph 1.x (LTS) workflow patterns for state management, routing, parallel execution, supervisor-worker, tool calling, checkpointing, human-in-loop, streaming (v2 format), subgraphs, and functional API. Use when building LangGraph pipelines, multi-agent systems, or AI workflows.
yonatangross/orchestkit 143
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python-backend
Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.
yonatangross/orchestkit 143
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distributed-systems
Distributed systems patterns for locking, resilience, idempotency, and rate limiting. Use when implementing distributed locks, circuit breakers, retry policies, idempotency keys, token bucket rate limiters, or fault tolerance patterns.
yonatangross/orchestkit 143
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issue-progress-tracking
Auto-updates GitHub issues with commit progress. Use when starting work on an issue, tracking progress during implementation, or completing work with a PR.
yonatangross/orchestkit 143
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design-to-code
Mockup-to-component pipeline using Google Stitch, 21st.dev, and Storybook MCP. Accepts screenshots, descriptions, or URLs as input and produces production-ready React components. Checks existing Storybook components before generating, orchestrates design extraction via Stitch MCP, component matching via 21st.dev registry, adaptation to project design tokens, and self-healing verification via run-story-tests. Use when converting visual designs to code, implementing UI from mockups, or building components from screenshots.
yonatangross/orchestkit 143
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prioritization
Prioritization frameworks — RICE, WSJF, ICE, MoSCoW, and opportunity cost scoring for backlog ranking. Use when prioritizing features, comparing initiatives, justifying roadmap decisions, or evaluating trade-offs between competing work items.
yonatangross/orchestkit 143
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doctor
OrchestKit doctor for health diagnostics. Use when running checks on plugin health, diagnosing problems, or troubleshooting issues.
yonatangross/orchestkit 143
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vite-advanced
Advanced Vite 8 patterns including Rolldown-powered builds, advancedChunks, Environment API, plugin development, SSR configuration, library mode, and build optimization. Use when customizing build pipelines, creating plugins, or configuring multi-environment builds.
yonatangross/orchestkit 143
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competitive-analysis
Porter's Five Forces, SWOT analysis, and competitive landscape mapping. Use when analyzing market position, evaluating competitive threats, building battlecards, or assessing industry dynamics.
yonatangross/orchestkit 143
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brainstorm
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
yonatangross/orchestkit 143
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multimodal-llm
Vision, audio, video generation, and multimodal LLM integration patterns. Use when processing images, transcribing audio, generating speech, generating AI video (Kling, Sora, Veo, Runway), or building multimodal AI pipelines.
yonatangross/orchestkit 143
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figma-design-handoff
Figma-to-code design handoff patterns including Figma Variables to design tokens pipeline, component spec extraction, Dev Mode inspection, Auto Layout to CSS Flexbox/Grid mapping, and visual regression with Applitools. Use when converting Figma designs to code, documenting component specs, setting up design-dev workflows, or comparing production UI against Figma designs.
yonatangross/orchestkit 143
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multi-surface-render
Multi-surface rendering with json-render — same JSON spec produces React components, PDFs, emails, Remotion videos, OG images, and more. Covers renderer target selection, registry mapping, and platform-specific APIs (renderToBuffer, renderToStream, renderToFile). Use when generating output for multiple platforms, creating PDF reports, email templates, demo videos, or social media images from a single component spec.
yonatangross/orchestkit 143
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verify
Comprehensive verification with parallel test agents. Use when verifying implementations or validating changes.
yonatangross/orchestkit 143
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interaction-patterns
UI interaction design patterns for skeleton loading, infinite scroll with accessibility, progressive disclosure, modal/drawer/inline selection, drag-and-drop with keyboard alternatives, tab overflow handling, and toast notification positioning. Use when implementing loading states, content pagination, disclosure patterns, overlay components, reorderable lists, or notification systems.
yonatangross/orchestkit 143
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react-server-components-framework
Use when building Next.js 16+ apps with React Server Components. Covers App Router, Cache Components (replacing experimental_ppr), streaming SSR, Server Actions, and React 19 patterns for server-first architecture.
yonatangross/orchestkit 143
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assess
Assesses and rates quality 0-10 with pros/cons analysis. Use when evaluating code, designs, or approaches.
yonatangross/orchestkit 143
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chain-patterns
Chain patterns for CC 2.1.71 pipelines — MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building multi-phase pipeline skills. Loaded via skills: field by pipeline skills (fix-issue, implement, brainstorm, verify). Not user-invocable.
yonatangross/orchestkit 143
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create-pr
Creates GitHub pull requests with validation. Use when opening PRs or submitting code for review.
yonatangross/orchestkit 143
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portless
Named .localhost URLs for local development with portless. Eliminates port collisions, enables stable URLs for agents, integrates with emulate for API emulation aliases and git worktrees for branch-named subdomains. Use when setting up local dev environments, configuring agent-accessible URLs, or running multi-service dev setups. Do NOT use for production deployments, CI environments (set PORTLESS=0), or DNS/hosting configuration.
yonatangross/orchestkit 143
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agent-orchestration
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
yonatangross/orchestkit 143
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ai-ui-generation
AI-assisted UI generation patterns for json-render, v0, Bolt, and Cursor workflows. Covers prompt engineering for component generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
yonatangross/orchestkit 143
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memory
Read-side memory operations: search, recall, load, sync, history, visualize. Use when searching past decisions, loading session context, or viewing the knowledge graph.
yonatangross/orchestkit 143
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feedback
Manages OrchestKit feedback, usage analytics, learning preferences, and privacy settings. Use when reviewing patterns, pausing learning, or managing consent.
yonatangross/orchestkit 143