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SkillsMP는 yonatangross/orchestkit에서 148개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
yonatangross/orchestkit수집된 skill 148개 중 40개를 표시합니다.
Evals-first error analysis for LLM apps: clusters real Langfuse or JSONL traces into a human-confirmed failure taxonomy with counts, then recommends binary pass/fail evals for recurring named modes. Use to learn what to measure before writing evals. Not for…
원문 언어: 영어
Error pattern analysis and troubleshooting for Claude Code sessions. Categorizes errors (network, auth, model, tool, memory, permission) with known resolution patterns, searches memory for prior occurrences, and suggests recovery steps. Delegates to…
원문 언어: 영어
Diff-aware AI browser testing — reads the git diff, maps changes to affected pages via the route map, generates a targeted test plan, and executes it via agent-browser (Rust daemon + CDP, ARIA-tree-first) with pass/fail reporting. Use when testing UI changes,…
원문 언어: 영어
Multi-angle codebase exploration spawning 3-5 parallel agents for code structure, data flow, architecture patterns, and health assessment. Generates ASCII visualizations, import graphs, and design pattern detection with cross-session memory storage. Use when…
원문 언어: 영어
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…
원문 언어: 영어
Fixes GitHub issues using parallel analysis agents for root cause investigation, code exploration, and regression detection. Reads issue context from gh CLI, searches codebase and memory for related patterns, generates a fix with tests, and links the…
원문 언어: 영어
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.
원문 언어: 영어
Render an answer as ASCII art plus semantic emojis inline with no setup questions: one render per reply, verdict first. Use for any answer with shape: status, inventories, audits, budgets, comparisons, rankings, pipelines, 'what is using X', or any ad-hoc…
원문 언어: 영어
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.
원문 언어: 영어
OrchestKit help directory with categorized skill listings. Use when discovering skills for a task, finding the right workflow, or browsing capabilities.
원문 언어: 영어
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.
원문 언어: 영어
Full-power feature implementation using parallel subagents for backend, frontend, testing, and security, with worktree isolation and quality verification in one workflow. Chains with /ork:cover for tests and /ork:verify for validation. Use when asked to…
원문 언어: 영어
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…
원문 언어: 영어
GitHub issue workflow ceremony using gh CLI — labels issues as in-progress, creates feature branches (issue/N-description), commits with issue references, posts progress comments, and links PRs with Closes #N. Keeps issues in sync with development work. Use…
원문 언어: 영어
LangGraph 1.x (LTS) Python workflow patterns for state management, delta channels, resilience (node timeouts, error handlers, graceful drain), routing, parallel execution, supervisor-worker, tool calling, checkpointing, human-in-loop, streaming (v2 format),…
원문 언어: 영어
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.
원문 언어: 영어
TAM/SAM/SOM market sizing with top-down and bottom-up estimation methods, cross-validation of assumptions, and divergence reconciliation. Generates investor-ready materials with growth projections and confidence intervals. Use when estimating addressable…
원문 언어: 영어
MCP server building, advanced patterns, and security hardening. Use when building MCP servers, implementing tool handlers, choosing a transport, adding OAuth authentication, wiring MCP Apps UI with @mcp-ui, hardening MCP security, or debugging MCP…
원문 언어: 영어
Memory retrieval internals: knowledge graph orchestration with entity extraction, natural language query parsing, deduplication (>85% similarity), and cross-reference boosting over unified recency, relevance, and authority ranking. Use when designing or…
원문 언어: 영어
Read-side memory operations on the knowledge graph: search past decisions and patterns, load session context, view decision timelines, render Mermaid graph visualizations. Subcommands: search, load, history, viz, status. Use when finding or reviewing what…
원문 언어: 영어
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…
원문 언어: 영어
Vision, audio, video generation, and multimodal LLM integration patterns. Use when processing images, transcribing audio, generating speech, generating AI video (Kling v3, Sora 2, Veo 3.1 std/lite/fast, Runway Gen-4.5 via `gen4_turbo`), or building multimodal…
원문 언어: 영어
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.
원문 언어: 영어
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,…
원문 언어: 영어
Decomposes a PRD, issue, or spec into a copy-pasteable single `/goal until ..., or stop after N turns` line. Use when running /goal against a spec, to reduce acceptance criteria to AND-joined boolean assertions.
원문 언어: 영어
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.
원문 언어: 영어
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.
원문 언어: 영어
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…
원문 언어: 영어
Production Python async patterns including asyncio TaskGroup, FastAPI dependency injection and middleware, SQLAlchemy 2.0 async sessions, and database connection pool tuning. Python 3.11+ runtime concerns such as ExceptionGroup, cancellation semantics, and…
원문 언어: 영어
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.
원문 언어: 영어
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.
원문 언어: 영어
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.
원문 언어: 영어
Automates GitHub releases with semantic versioning, changelog generation from merged PRs, and gh CLI integration. Supports draft, prerelease, and standard release workflows with task-tracked multi-phase execution. Use when creating releases, tagging versions,…
원문 언어: 영어
Write-side memory: stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Use when something worth persisting across sessions was just learned or decided. To search or read existing…
원문 언어: 영어
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.
원문 언어: 영어
PR review using parallel specialized agents for code quality, security, testing, architecture, and performance analysis. Synthesizes findings into a review report with conventional comments (praise/issue/suggestion/nitpick) and approve or request-changes…
원문 언어: 영어
Right-sizes architecture to project scope, classifying projects into 6 tiers to prevent over-engineering. Use when designing architecture, selecting patterns, or detecting a project tier.
원문 언어: 영어
Security patterns for authentication, defense-in-depth, input validation, OWASP Top 10, LLM safety, and PII masking. Use when implementing auth flows, security layers, input sanitization, vulnerability prevention, prompt injection defense, or data redaction.
원문 언어: 영어
Personalized 7-phase onboarding wizard that scans the codebase, detects tech stack, recommends skills and MCP servers, and generates an improvement plan with readiness score. Includes safety checks and project-scoped configuration. Use when setting up…
원문 언어: 영어
Reference for the Storybook MCP server itself (@storybook/addon-mcp): 6 tools across 3 toolsets (dev, docs, testing), availability detection, and per-agent toolset filtering. Use when setting up the server or calling these tools directly against components…
원문 언어: 영어