Reference Skills
The 81 user-invocable:false skills auto-injected into agent context — the knowledge library behind OrchestKit agents.
What Are Reference Skills?
Reference skills are the 81 skills with user-invocable: false in their frontmatter. You never invoke them directly — they are automatically injected into agent context through three paths:
- Agent frontmatter — each agent declares the skills it needs; when the agent spawns, those skills load automatically.
- Command-skill composition — a command skill (e.g.
/ork:implement) pulls in reference skills via itsskills:field. - Keyword auto-suggest — the
skill-auto-suggesthook injects matching skills based on keywords in your prompt.
Skills are grouped below by the agent: field they declare. Skills with no agent: are cross-cutting — shared across agents or the core system.
Accessibility
Primary agent: accessibility-specialist
| Skill | Description |
|---|---|
accessibility | Accessibility patterns for WCAG 2.2 compliance, keyboard focus management, React Aria component patterns, cognitive inclusion, native HTML-first philosophy, and user preference honoring. Use when implementing screen reader support, keyboard navigation, ARIA patterns, focus traps, accessible component libraries, reduced motion, or cognitive accessibility. |
Backend & Distributed Systems
Primary agent: backend-system-architect
| Skill | Description |
|---|---|
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. |
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. |
architecture-patterns | Architecture validation and patterns for clean architecture, backend structure enforcement, project structure validation, test standards, and context-aware sizing. Use when designing system boundaries, enforcing layered architecture, validating project structure, defining test standards, or choosing the right architecture tier for project scope. |
distributed-systems | Distributed systems patterns for locking, resilience, idempotency, and rate limiting. Use when implementing distributed locks, circuit breakers, retry policies, idempotency keys, token bucket rate limiters, or fault tolerance patterns. |
domain-driven-design | DDD tactical patterns for complex business modeling including entities, value objects, aggregates, domain services, repositories, specifications, and bounded contexts. Python dataclass implementations with TypeScript alternatives. Use when building rich domain models, enforcing invariants, or separating domain logic from infrastructure. |
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+ examples with structured error handling. Use when building async services, FastAPI endpoints, or tuning database connection pools. |
CI/CD
Primary agent: ci-cd-engineer
| Skill | Description |
|---|---|
devops-deployment | Use when setting up CI/CD pipelines, containerizing applications, deploying to Kubernetes, or writing infrastructure as code. DevOps & Deployment covers GitHub Actions, Docker, Helm, and Terraform patterns. |
Code Quality
Primary agent: code-quality-reviewer
| Skill | Description |
|---|---|
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. |
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. |
Data Pipelines & RAG
Primary agent: data-pipeline-engineer
| Skill | Description |
|---|---|
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. |
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. |
Database
Primary agent: database-engineer
| Skill | Description |
|---|---|
database-patterns | Database design and migration patterns for Alembic migrations, schema design (SQL/NoSQL), and database versioning. Use when creating migrations, designing schemas, normalizing data, managing database versions, or handling schema drift. |
Debugging
Primary agent: debug-investigator
| Skill | Description |
|---|---|
errors | 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 debug-investigator agent for complex root cause analysis. Use when handling errors, fixing failures, or troubleshooting session issues. |
API Emulation
Primary agent: emulate-engineer
| Skill | Description |
|---|---|
emulate-seed | Generate emulate seed configs for stateful API emulation. Wraps Vercel's emulate tool for GitHub, Vercel, Google OAuth, Slack, Apple Auth, Microsoft Entra, AWS (S3/SQS/IAM), Okta, Clerk, Resend, Stripe, and MongoDB Atlas APIs. Not mocks — full state machines where create-a-PR-and-it-appears-in-the-list, send-an-email-and-retrieve-from-local-inbox. Use when setting up test environments, CI pipelines, integration tests, or offline development. |
Frontend Performance
Primary agent: frontend-performance-engineer
| Skill | Description |
|---|---|
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. |
Frontend & UI
Primary agent: frontend-ui-developer
| Skill | Description |
|---|---|
ai-ui-generation | AI-assisted UI generation patterns for json-render, v0.app, Google Stitch, Bolt Cloud, and Cursor workflows. Covers prompt engineering for component and full-stack app 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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
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. |
Genui Architect
Primary agent: genui-architect
| Skill | Description |
|---|---|
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 36 pre-built components, optimize specs with YAML mode, and apply the three edit modes (patch/merge/diff) for progressive updates. Use when building AI-generated UIs, defining component catalogs, or integrating json-render into React/Vue/Svelte/React Native/Ink/Next.js projects. |
LLM, RAG & AI
Primary agent: llm-integrator
| Skill | Description |
|---|---|
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. |
Multimodal Specialist
Primary agent: multimodal-specialist
| Skill | Description |
|---|---|
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. |
Product & Strategy
Primary agent: product-strategist
| Skill | Description |
|---|---|
business-case | Business case analysis with ROI, NPV, IRR, payback period, and TCO calculations for investment decisions. Use when building financial justification, cost-benefit analysis, build-vs-buy comparisons, or sensitivity analysis. |
competitive-analysis | Strategic analysis frameworks including Porter's Five Forces (industry attractiveness), SWOT (internal positioning), and competitive landscape mapping with battlecard generation. Produces competitor profiles, feature gap analysis, and positioning recommendations. Use when analyzing market position, evaluating threats, or building sales battlecards. |
market-sizing | 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 markets, validating opportunity size, or preparing pitch deck market slides. |
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. |
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. |
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. |
Python Performance
Primary agent: python-performance-engineer
| Skill | Description |
|---|---|
async-jobs | Async job processing patterns for background tasks, Celery workflows, task scheduling, retry strategies, and distributed task execution. Use when implementing background job processing, task queues, or scheduled task systems. |
Release Engineer
Primary agent: release-engineer
| Skill | Description |
|---|---|
documentation-patterns | Technical documentation patterns for READMEs, ADRs, API docs (OpenAPI 3.1), changelogs, and writing style guides. Use when creating project documentation, writing architecture decisions, documenting APIs, or maintaining changelogs. |
Security
Primary agent: security-auditor
| Skill | Description |
|---|---|
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. |
Testing
Primary agent: test-generator
| Skill | Description |
|---|---|
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-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. |
Web Research
Primary agent: web-research-analyst
| Skill | Description |
|---|---|
browser-tools | OrchestKit security wrapper for browser automation. Adds URL blocklisting, rate limiting, robots.txt enforcement, and ethical scraping guardrails on top of the upstream agent-browser skill. Use when automating browser workflows that need safety guardrails. |
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. |
LangGraph & Workflows
Primary agent: workflow-architect
| Skill | Description |
|---|---|
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. |
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. |
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. |
Cross-Cutting Skills
These skills do not declare an agent: field — they serve multiple agents or the core system.
| Skill | Description |
|---|---|
analytics | Queries local analytics across OrchestKit projects for agent usage, skill frequency, hook timing, team activity, session replay, cost estimation, and model delegation trends. Privacy-safe with hashed project IDs. Supports time-range filtering and comparative analysis. Use when reviewing performance, estimating costs, or understanding usage patterns. |
ascii-visualizer | ASCII diagram patterns for architecture, workflows, file trees, and data visualizations. Use when creating terminal-rendered diagrams, box-drawing layouts, progress bars, swimlanes, or blast radius visualizations. |
audit-activation | Audits OrchestKit sub-agent activation from real spawn telemetry — computes the generic-vs-specialist spawn split, flags dormant agents (never fired), and classifies each as fires/mis-triggered/niche. The agent-side analogue of audit-skills. Use when specialized agents feel under-used, before pruning the catalog, or after wiring new agent spawn paths. |
audit-full | Single-pass codebase analysis leveraging Opus 4.8 1M context for comprehensive security scanning, architecture review, and dependency auditing. Loads entire codebases for cross-file pattern detection and generates structured audit reports with severity-ranked findings. Use when you need whole-project analysis before releases or security reviews. |
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. |
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. |
chain-patterns | Chain patterns for CC 2.1.71 pipelines — MCP detection, handoff files, checkpoint-resume, worktree agents, CronCreate monitoring. Use when building multi-phase pipeline skills. Loaded via skills: field by pipeline skills (fix-issue, implement, brainstorm, verify). Not user-invocable. |
checkpoint-resume | Rate-limit-resilient pipeline with checkpoint/resume for long multi-phase sessions. Saves progress to .claude/pipeline-state.json after each phase. Use when starting a complex multi-phase task that risks hitting rate limits, when resuming an interrupted session, or when orchestrating work spanning commits, GitHub issues, and large file changes. |
configure | Interactive configuration wizard for OrchestKit plugin settings including MCP server enablement, hook permissions, keybindings, and installation presets (Complete/Standard/Lite). Supports preset shortcuts, per-category skill customization, and webhook configuration. Use when customizing plugin behavior or managing settings. |
demo-producer | Universal demo video creator for skills, agents, plugins, tutorials, CLI commands, and code walkthroughs. Generates scripts, storyboards, VHS terminal recordings, and Remotion video compositions with task-tracked production phases. Use when producing video showcases, marketing content, or terminal recordings. |
feedback | Manages OrchestKit learning system including feedback status, usage pattern tracking, and privacy/analytics consent. Supports pause/resume learning, data export, privacy policy display, and bug reporting. Tracks learned patterns and agent performance metrics. Use when reviewing learned patterns, pausing learning, or managing data consent. |
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. |
issue-progress-tracking | 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 when starting work on an issue, tracking progress, or completing work with a PR. |
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. |
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, ChatGPT, VS Code Copilot, Goose, and Postman conversations. Covers createMcpApp(), registerJsonRenderTool(), registerJsonRenderResource(), CSP config, JSON Patch 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. |
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. |
multi-surface-render | Multi-surface rendering with json-render — same JSON spec produces React web, Next.js apps, React Native, Ink terminal UIs, PDFs, emails, Remotion videos, OG images, and 3D scenes. 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. |
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. |
portless | Named HTTPS .localhost URLs for local development with portless (v0.15.x). Eliminates port collisions, enables stable URLs for agents, integrates with emulate for API emulation aliases, git worktrees for branch-named subdomains, LAN mode (--lan) for mDNS .local hostnames reachable across devices, Tailscale sharing (--tailscale / --funnel), and OS startup-service install for boot persistence. Use when setting up local dev environments, configuring agent-accessible URLs, running multi-service dev setups, or testing from phones/tablets on the same wifi. Do NOT use for production deployments, CI environments (set PORTLESS=0), or DNS/hosting configuration. |
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. |
release-checklist | Sequential release gate validating build success, test suite, security checks, type checking, manifest counts consistency, and changelog presence. Each step reports pass/fail with remediation guidance. Manages version bumping, staging, and pre-push confirmation. Use when preparing a release. |
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. |
scope-appropriate-architecture | Right-sizes architecture to project scope. Prevents over-engineering by classifying projects into 6 tiers and constraining pattern choices accordingly. Use when designing architecture, selecting patterns, or when brainstorm/implement detect a project tier. |
skill-evolution | Tracks skill usage patterns, edit frequency, and success rates to suggest improvements and optimizations. Manages skill versioning with safe rollback capability and confidence scoring for suggestions. Use when reviewing skill performance, applying auto-suggested changes, or rolling back problematic versions. |
storybook-mcp-integration | Storybook MCP server integration for component-aware AI development. Covers 6 tools across 3 toolsets (dev, docs, testing): component discovery via list-all-documentation/get-documentation, story previews via preview-stories, and automated testing via run-story-tests. Use when generating components that should reuse existing Storybook components, running component tests via MCP, or previewing stories in chat. |
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. |
upgrade-assessment | Evaluates platform upgrade readiness across Claude model versions, CC releases, and OrchestKit updates with 6-dimensional assessment. Researches target versions, detects current environment, produces structured migration plan with risk scores. Use when planning major version transitions or evaluating upgrade impact. |
validate-counts | Validates hook, skill, and agent counts are consistent across CLAUDE.md, hooks.json, manifests, and source directories. Use when counts may be stale after adding or removing components, before releases, or when CLAUDE.md Project Overview looks wrong. |
How Reference Skills Get to Agents
The link between a reference skill and its agent is bidirectional: the skill's agent: field names its owning agent, and the agent's skills: array lists the skills it loads. When an agent spawns, Claude Code injects each listed skill's content into the agent's context window.
What's Next
- Command Skills — the commands that orchestrate these reference skills.
- Composing Skills Into Workflows — how everything fits together.
- Writing Skills — add reference skills for your own domain.
18 Commands You Can Invoke
Every /ork:X command skill in OrchestKit -- grouped by category with descriptions and usage examples.
Backend Skills
API design, databases, Python, async patterns, distributed systems.
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