Sponsored by

Find leads on Reddit on auto pilot

Agent skills
langgraph

Topic: langgraph

393 skills in this topic.

upgrade-assessment Assess platform upgrade readiness for Claude model and CC version changes. Use when evaluating upgrades.
yonatangross/orchestkit 143
mcp-patterns MCP server building, advanced patterns, and security hardening. Use when building MCP servers, implementing tool handlers, adding authentication, creating interactive UIs, hardening MCP security, or debugging MCP integrations.
yonatangross/orchestkit 143
market-sizing TAM, SAM, SOM market sizing with top-down and bottom-up methods. Use when estimating addressable market, validating opportunity size, sizing new segments, or preparing investor pitch materials.
yonatangross/orchestkit 143
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
performance Performance optimization patterns covering Core Web Vitals, React render optimization, lazy loading, image optimization, backend profiling, LLM inference, and sustainability UX. Use when improving page speed, debugging slow renders, optimizing bundles, reducing image payload, profiling backend, deploying LLMs efficiently, or reducing digital carbon footprint.
yonatangross/orchestkit 143
notebooklm NotebookLM integration patterns for external RAG, research synthesis, studio content generation (audio, cinematic video, slides, infographics, mind maps), and knowledge management. Use when creating notebooks, adding sources, generating audio/video, or querying NotebookLM via MCP.
yonatangross/orchestkit 143
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
mcp-visual-output Interactive MCP visual output via @json-render/mcp. Upgrade plain JSON tool responses to interactive dashboards rendered in sandboxed iframes inside Claude, Cursor, and ChatGPT conversations. Covers createMcpApp(), registerJsonRenderTool(), CSP config, streaming, and dashboard component patterns. Use when building MCP servers that return visual output, upgrading existing MCP tools with interactive UI, or creating eval/monitoring dashboards.
yonatangross/orchestkit 143
product-frameworks Product management frameworks for business cases, market analysis, strategy, prioritization, OKRs/KPIs, personas, requirements, and user research. Use when building ROI projections, competitive analysis, RICE scoring, OKR trees, user personas, PRDs, or usability testing plans.
yonatangross/orchestkit 143
product-analytics A/B test evaluation, cohort retention analysis, funnel metrics, and experiment-driven product decisions. Use when analyzing experiments, measuring feature adoption, diagnosing conversion drop-offs, or evaluating statistical significance of product changes.
yonatangross/orchestkit 143
ui-components UI component library patterns for shadcn/ui and Radix Primitives. Use when building accessible component libraries, customizing shadcn components, using Radix unstyled primitives, or creating design system foundations.
yonatangross/orchestkit 143
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
rag-retrieval Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, embedding documents, implementing hybrid search, contextual retrieval, HyDE, agentic RAG, multimodal RAG, query decomposition, reranking, or pgvector search.
yonatangross/orchestkit 143
quality-gates Use when assessing task complexity, before starting complex tasks, when stuck after multiple attempts, or reviewing code against best practices. Provides quality-gates scoring (1-5), escalation workflows, and pattern library management.
yonatangross/orchestkit 143
responsive-patterns Responsive design with Container Queries, fluid typography, cqi/cqb units, subgrid, intrinsic layouts, foldable devices, and mobile-first patterns for React applications. Use when building responsive layouts or container queries.
yonatangross/orchestkit 143
release-sync Sync release content to NotebookLM and HQ Knowledge Base after tagging a new version. Reads CHANGELOG, CLAUDE.md, and hook README, then updates notebook sources and ingests to knowledge base.
yonatangross/orchestkit 143
testing-e2e End-to-end testing patterns with Playwright — page objects, AI agent testing, visual regression, accessibility testing with axe-core, and CI integration. Use when writing E2E tests, setting up Playwright, implementing visual regression, or testing accessibility.
yonatangross/orchestkit 143
storybook-testing Storybook 10 testing patterns with Vitest integration, ESM-only distribution, CSF3 typesafe factories, play() interaction tests, Chromatic TurboSnap visual regression, module automocking, accessibility addon testing, and autodocs generation. Use when writing component stories, setting up visual regression testing, configuring Storybook CI pipelines, or migrating from Storybook 9.
yonatangross/orchestkit 143
review-pr PR review with parallel specialized agents. Use when reviewing pull requests or code.
yonatangross/orchestkit 143
remember Stores decisions and patterns in knowledge graph. Use when saving patterns, remembering outcomes, or recording decisions.
yonatangross/orchestkit 143
testing-unit Unit testing patterns for isolated business logic tests — AAA pattern, parametrized tests (test.each, @pytest.mark.parametrize), fixture scoping (function/module/session), mocking with MSW/VCR at network level, and test data management with factories (FactoryBoy, faker-js). Use when writing unit tests, setting up mocks, structuring test data, optimizing test speed, choosing fixture scope, or reducing test boilerplate. Covers Vitest, Jest, pytest.
yonatangross/orchestkit 143
testing-integration Integration and contract testing patterns — API endpoint tests, component integration, database testing, Pact contract verification, property-based testing, and Zod schema validation. Use when testing API boundaries, verifying contracts, or validating cross-service integration.
yonatangross/orchestkit 143
task-dependency-patterns Task Management patterns with TaskCreate, TaskUpdate, TaskGet, TaskList tools. Decompose complex work into trackable tasks with dependency chains. Use when managing multi-step implementations, coordinating parallel work, or tracking completion status.
yonatangross/orchestkit 143
storybook-mcp-integration Storybook MCP server integration for component-aware AI development. Covers 6 tools across 3 toolsets (dev, docs, testing): component discovery via list-all-documentation/get-documentation, story previews via preview-stories, and automated testing via run-story-tests. Use when generating components that should reuse existing Storybook components, running component tests via MCP, or previewing stories in chat.
yonatangross/orchestkit 143