memory-fabric
Knowledge graph orchestration layer with entity extraction, natural language query parsing, deduplication (>85% similarity), and cross-reference boosting. Unifies search results ranked by recency, relevance, and authority. Use when designing memory retrieval, building entity graphs, or optimizing knowledge graph queries.
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.
multimodal-llm
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 AI pipelines.
multi-surface-render
Multi-surface rendering with json-render — one JSON spec produces React web, Next.js, React Native, Ink terminal UIs, PDFs, emails, Remotion videos, OG images, and 3D scenes. Covers renderer target selection, registry mapping, and platform APIs (renderToBuffer, renderToStream, renderToFile). Use when generating output for several platforms or creating PDF reports, email templates, demo videos, or social images from one component spec.
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.
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.
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.
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.
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.
python-backend
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 session rollback. Use when building async services, wiring FastAPI dependencies, or tuning database connection pools. Runtime implementation layer, not the API wire contract.
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.
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.
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.
release-management
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, or publishing changelogs.
remember
Stores decisions, patterns, and outcomes in the MCP memory knowledge graph as entities with typed observations and relations. Supports recording architectural decisions, anti-patterns, tool preferences, workflow outcomes, and project conventions that persist across sessions. Use when saving patterns, remembering outcomes, recording decisions, or building institutional knowledge.
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.
review-pr
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 verdict. Use when reviewing pull requests, conducting security audits, or validating changes before merge.
scope-appropriate-architecture
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.
security-patterns
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.
setup
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 OrchestKit for a new project or rescanning after major changes.
storybook-mcp-integration
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 that already exist. For the end-to-end pipeline that turns a mockup into a new component and consumes these tools as one stage, use design-to-code.
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.
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.
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.
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.
testing-llm
LLM and AI testing patterns — mock responses, evaluation with DeepEval/RAGAS, structured output validation, and agentic test patterns (generator, healer, planner). Use when testing AI features, validating LLM outputs, or building evaluation pipelines.
testing-patterns
Redirect — testing-patterns was split into 5 focused sub-skills. Use when looking for testing-patterns, writing tests, or test automation. Redirects to testing-unit, testing-e2e, testing-integration, testing-llm, or testing-perf.
testing-perf
Performance and load testing patterns — k6 load tests, Locust stress tests, pytest execution optimization (xdist parallel, plugins), test type classification, and performance benchmarking. Use when writing load tests, optimizing test execution speed, or setting up pytest infrastructure.
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.
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.
user-research
User personas, customer journey maps, interview guides, usability testing, and card sorting. Use when building user understanding, mapping customer experiences, planning user research sessions, or defining Jobs-to-Be-Done.
verify
Grade work that already exists and decide whether it can merge. Runs the project's current unit, integration, and E2E suites plus security scanning and type checking, scores every dimension 0-10, and returns a merge verdict with a VERIFIED-vs-CLAIMED evidence manifest. Writes no test files and edits no source. Use when verifying changes are ready to merge. Use /ork:cover instead when the tests still have to be written.
visualize-plan
Renders planned changes — architecture and before/after comparisons, risk heat maps, execution order, dependency graphs, impact metrics — in your chosen output format (ASCII + emojis, an interactive HTML playground, or a NotebookLM infographic). Stores visualizations in memory for cross-session reference. Use when reviewing implementation plans, comparing approaches, assessing risk, or analyzing change propagation.
vite-advanced
Advanced Vite 8 patterns including Rolldown-powered builds, advancedChunks, Environment API, plugin development, SSR configuration, library mode, and build optimization. Use when customizing build pipelines, creating plugins, or configuring multi-environment builds.
web-research-workflow
Unified decision tree for web research and competitive monitoring. Auto-selects WebFetch, Tavily, or agent-browser based on target site characteristics and available API keys. Includes competitor page tracking, snapshot diffing, and change alerting. Use when researching web content, scraping, extracting raw markdown, capturing documentation, or monitoring competitor changes.
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.
zustand-patterns
Reference for Zustand 5.x state management including slices, middleware, Immer, useShallow, persistence, selectors, and devtools integration. Documents 7 core patterns with TypeScript examples and anti-patterns. Use when building React state management with Zustand instead of Redux.
audit-activation
Audits sub-agent activation from explicit consumer telemetry roots. It separates attempted, started, completed, and unattributed events, reports coverage, and identifies observed zero starts without making an estate-wide dormancy claim. Use when specialized agents feel under-used, before pruning the catalog, or after wiring new agent spawn paths.
auto
Intent-classified router, the front door to OrchestKit and the DEFAULT entry point for any goal-shaped request. Classifies a plain-English goal and routes it to the right specialist skill. Routing is never overhead, so use it even when the target skill seems obvious; skip only when already executing inside another skill (no recursion). Triggers on: auto, do this, figure out, just make, I want, help me, fix, build, improve, any goal description.
ci-debug
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for org-wide CI sweeps (that's /status) or for app-level test failures (the playbook is CI-infra-specific).
ci-sentinel
Daily autonomous classifier for failing PRs across your repos. Runs /ci-debug headless against every open PR with red required checks, posts the verdict as a collapsed PR comment, and appends to a per-repo .sentinel/ledger.jsonl. v1 is propose-don't-apply — NEVER auto-pushes a fix. Use when you're tired of /status sweeps catching the same 10 CI failure patterns over and over.
design-import
Scaffolds React components from a Claude Design handoff bundle and stops at files on disk: no stories, no tests, no pull request. Use when handed a claude.ai/design URL or a local bundle file; when that same scaffold should carry on through test generation, browser verification and an opened PR, run /ork:design-ship instead.
design-ship
One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to disk, run /ork:design-import instead.
design-stylecards
Declarative catalog of named aesthetic recipes — exact shadow stacks, glass surfaces, gradient treatments, and type scales as copy-paste values with Use-When and Avoid rules. Use when the user asks for polished elevation, glassmorphism, a border gradient, a mesh background, or any 'make it look like X' request where taste should come from a versioned recipe instead of being reinvented per session.
dev
One-command dev loop boot. Spins up portless (named HTTPS subdomain), emulate (stateful API mocks), the project's dev server, and an agent-browser session, all keyed to the current git branch. Use when starting a feature branch, switching worktrees, or returning to a project after a break. Skips silently with install hints when prerequisite binaries are missing.
dream
Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use memory).
glyph
Render an answer as ASCII art plus semantic emojis inline, right now, with no setup questions: one render per reply, up to about 50 lines, verdict first. Use for any answer with shape: status, inventories, audits, budgets, comparisons, rankings, pipelines, 'what is using X', or any ad-hoc 'show me X visually' ask. Not for definitions, conceptual explanations, or one-sentence and one-paragraph asks; those have no shape to draw. For a full multi-artifact plan playground, use visualize-plan instead.
ork-assess
Assess a code change, design, architecture, workflow, or competing options against explicit criteria and evidence. Use when a request asks to assess, rate, compare, identify trade-offs, evaluate readiness, or decide whether an approach is good enough. Do not use for a full pull-request review or to implement a chosen solution.
ork-brainstorm
Compare plausible implementation, architecture, product, or operational approaches before committing to one. Use when a request asks to brainstorm, think through options, choose an approach, evaluate trade-offs, or resolve significant uncertainty before implementation. Do not use for an already specified mechanical change.
ork-explore
Map an unfamiliar codebase, feature, architecture, data flow, or operational path with file-backed evidence. Use when a request asks how a system works, where behavior lives, what changed, which dependencies matter, or for onboarding before a change. Do not use to implement or fix the code.
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