Topic: llm
10,059 skills in this topic.
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remember
Stores decisions and patterns in knowledge graph. Use when saving patterns, remembering outcomes, or recording decisions.
yonatangross/orchestkit 143
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domain-driven-design
Domain-Driven Design tactical patterns for complex business domains. Use when modeling entities, value objects, domain services, repositories, or establishing bounded contexts.
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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llm-integration
LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.
yonatangross/orchestkit 143
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design-system-tokens
Design token management with W3C Design Token Community Group specification, three-tier token hierarchy (global/alias/component), OKLCH color spaces, Style Dictionary transformation, and dark mode theming. Use when creating design token files, implementing theme systems, managing token versioning, or building design-to-code pipelines.
yonatangross/orchestkit 143
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write-prd
Write PRD — Product Requirements Documents with structured 8-section templates, user stories, acceptance criteria, and value proposition validation. Use when writing PRDs, defining product requirements, creating user stories with INVEST criteria, or building go/no-go decision frameworks.
yonatangross/orchestkit 143
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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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commit
Creates commits with conventional format and validation. Use when committing changes or generating commit messages.
yonatangross/orchestkit 143
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code-review-playbook
Use this skill when conducting or improving code reviews. Provides structured review processes, conventional comments patterns, language-specific checklists, and feedback templates. Use when reviewing PRs or standardizing review practices.
yonatangross/orchestkit 143
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fix-issue
Fixes GitHub issues with parallel analysis. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues.
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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errors
Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.
yonatangross/orchestkit 143
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monitoring-observability
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse v4 LLM tracing (as_type, score_current_span, should_export_span, LangfuseMedia), and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
yonatangross/orchestkit 143
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skill-evolution
Analyzes skill usage patterns and suggests improvements. Use when reviewing skill performance, applying auto-suggested changes, or rolling back versions.
yonatangross/orchestkit 143
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json-render-catalog
json-render component catalog patterns for AI-safe generative UI. Define Zod-typed catalogs that constrain what AI can generate, use @json-render/shadcn for 29 pre-built components, optimize specs for token efficiency with YAML mode. Use when building AI-generated UIs, defining component catalogs, or integrating json-render into React/Vue/Svelte/React Native projects.
yonatangross/orchestkit 143
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design-context-extract
Extract design DNA from existing app screenshots or live URLs using Google Stitch. Produces color palettes, typography specs, spacing tokens, and component patterns as design-tokens.json or Tailwind config. Use when auditing an existing design, creating a design system from a live app, or ensuring new pages match an established visual identity.
yonatangross/orchestkit 143
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demo-producer
Creates polished demo videos for skills, tutorials, and CLI demonstrations. Use when producing video showcases, marketing content, or terminal recordings.
yonatangross/orchestkit 143
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architecture-decision-record
Use this skill when documenting significant architectural decisions. Provides ADR templates following the Nygard format with sections for context, decision, consequences, and alternatives. Use when writing ADRs, recording decisions, or evaluating options.
yonatangross/orchestkit 143
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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
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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
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api-design
API design patterns for REST/GraphQL framework design, versioning strategies, and RFC 9457 error handling. Use when designing API endpoints, choosing versioning schemes, implementing Problem Details errors, or building OpenAPI specifications.
yonatangross/orchestkit 143
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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
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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
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animation-motion-design
Animation and motion design patterns using Motion library (formerly Framer Motion) and View Transitions API. Use when implementing component animations, page transitions, micro-interactions, gesture-driven UIs, or ensuring motion accessibility with prefers-reduced-motion.
yonatangross/orchestkit 143