Sponsored by

Find leads on Reddit on auto pilot

Agent skills
claude-code

Topic: claude-code

35,830 skills in this topic.

errors Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.
yonatangross/orchestkit 143
expect Diff-aware AI browser testing — analyzes git changes, generates targeted test plans, and executes them via agent-browser. Reads git diff to determine what changed, maps changes to affected pages via route map, generates a test plan scoped to the diff, and runs it with pass/fail reporting. Use when testing UI changes, verifying PRs before merge, running regression checks on changed components, or validating that recent code changes don't break the user-facing experience.
yonatangross/orchestkit 143
explore explore — Deep codebase exploration with parallel agents. Use when exploring a repo, discovering architecture, finding files, or analyzing design patterns.
yonatangross/orchestkit 143
feedback Manages OrchestKit feedback, usage analytics, learning preferences, and privacy settings. Use when reviewing patterns, pausing learning, or managing consent.
yonatangross/orchestkit 143
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
fix-issue Fixes GitHub issues with parallel analysis. Use when debugging errors, resolving regressions, fixing bugs, or triaging issues.
yonatangross/orchestkit 143
github-operations GitHub CLI operations for issues, PRs, milestones, and Projects v2. Covers gh commands, REST API patterns, and automation scripts. Use when managing GitHub issues, PRs, milestones, or Projects with gh.
yonatangross/orchestkit 143
golden-dataset Golden dataset lifecycle patterns for curation, versioning, quality validation, and CI integration. Use when building evaluation datasets, managing dataset versions, validating quality scores, or integrating golden tests into pipelines.
yonatangross/orchestkit 143
help OrchestKit help directory with categorized skill listings. Use when discovering skills for a task, finding the right workflow, or browsing capabilities.
yonatangross/orchestkit 143
i18n-date-patterns Implements internationalization (i18n) in React applications. Covers user-facing strings, date/time handling, locale-aware formatting, ICU MessageFormat, and RTL support. Use when building multilingual UIs or formatting dates/currency.
yonatangross/orchestkit 143
implement Full-power feature implementation with parallel subagents. Use when implementing, building, or creating features.
yonatangross/orchestkit 143
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
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
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
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
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
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
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
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
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
memory-fabric Knowledge graph memory orchestration - entity extraction, query parsing, deduplication, and cross-reference boosting. Use when designing memory orchestration.
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
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
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