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Topic: agents

2,643 skills in this topic.

analytics Query cross-project usage analytics. Use when reviewing agent, skill, hook, or team performance across OrchestKit projects. Also replay sessions, estimate costs, and view model delegation trends.
yonatangross/orchestkit 143
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
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
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
assess Assesses and rates quality 0-10 with pros/cons analysis. Use when evaluating code, designs, or approaches.
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
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
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
release-management GitHub release workflow with semantic versioning, changelogs, and release automation using gh CLI. Use when creating releases, tagging versions, or publishing changelogs.
yonatangross/orchestkit 143
release-checklist Validates release readiness with gated checklist — build, test, count validation, changelog, version bump. Use when preparing a release.
yonatangross/orchestkit 143
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
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
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
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
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
presentation-builder Creates zero-dependency, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web slides, or create a slide deck for a talk, pitch, or tutorial. Generates single self-contained HTML files with inline CSS/JS.
yonatangross/orchestkit 143
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
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
okr-design OKR trees, KPI dashboards, North Star Metric, leading/lagging indicators, and experiment design. Use when setting team goals, defining success metrics, building measurement frameworks, or designing A/B experiment guardrails.
yonatangross/orchestkit 143
bare-eval Run isolated eval and grading calls using CC 2.1.81 --bare mode. Constructs claude -p --bare invocations for skill evaluation, trigger testing, and LLM grading without plugin/hook interference. Use when running eval pipelines, grading skill outputs, benchmarking prompt quality, or testing trigger accuracy in isolation.
yonatangross/orchestkit 143
audit-skills Audits all OrchestKit skills for quality, completeness, and compliance with authoring standards. Use when checking skill health, before releases, or after bulk skill edits to surface SKILL.md files that are too long, have missing frontmatter, lack rules/references, or are unregistered in manifests.
yonatangross/orchestkit 143
audit-full Full-codebase audit using 1M context window. Security, architecture, and dependency analysis in a single pass. Use when you need whole-project analysis.
yonatangross/orchestkit 143