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.
git clone --depth 1 https://github.com/yonatangross/orchestkit /tmp/ork-explore && cp -r /tmp/ork-explore/plugins/ork-codex/skills/ork-explore ~/.claude/skills/ork-exploreSKILL.md
# Ork Explore Stay read-only. Start with the task boundary, repository instructions, entry points, and the smallest searches that can prove the execution path. Cite files and symbols for every material claim; distinguish confirmed behavior from inference. When the path runs through a third-party library or framework, read its current documentation with the context7 MCP server: call `resolve-library-id` to get the library ID, then `query-docs`. Those are the only two tools it exposes. A recalled API detail you could not confirm belongs in the unknowns list, not in the map. Explore in one context by default. Fan out only for three or more independent questions such as structure, data flow, tests, and deployment. Use a flat fan-out, make each assignment bounded and read-only, and ask for concise evidence rather than proposed fixes. Prefer `ork_explorer` when installed; otherwise use Codex's built-in `explorer`. Return a compact map: entry points, important components and dependencies, tests/observability, risks or unknowns, and the next smallest investigation. Do not change files or turn the map into an implementation plan unless asked.
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.
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.
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.
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.
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.
API contract design for REST and GraphQL, covering resource shape, URL and header versioning with deprecation windows, RFC 9457 Problem Details error handling, and OpenAPI specs. Use when specifying the wire contract an endpoint exposes, choosing a versioning scheme, or standardizing error response bodies across services. Framework-agnostic protocol layer, not runtime implementation.
ADR templates in the Nygard format with context, decision, consequences, and alternatives. Use when writing ADRs, recording an architectural decision, or evaluating options.
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.