Skill UI

Build and deploy the same feature consistently across web, iOS, Android, and desktop using API-first architecture, shared design systems, and parallel implementation strategies to achieve cross-platform feature parity.

A comprehensive guide providing best practices and architectural patterns for modern full-stack development using Next.js 14+ App Router. Covers advanced topics like Server Components, efficient data fetching, handling parallel routes, and implementing full-stack features with Server Actions for scalable React applications.

Plans first, then orchestrates dynamic multi-agent workflows with adversarial verification via a local odw daemon or native fallback. Supports 16-100 parallel agents, sandboxed scripts, SQLite checkpoints, and crash-resume for tasks spanning many files or items.

Open Dynamic Workflows (ODW) is an advanced, open-source engine designed to manage complex coding tasks using multiple AI agents. It operates in three stages: planning the task into parallel subtasks, orchestrating various coding agents (like Codex or Antigravity) to work concurrently, and finally, performing an adversarial verification pass to challenge and validate the combined output before merging. It supports multiple model providers and is ideal for structured, high-reliability software development.

Coordinate focused subagents on substantial work while maintaining non-overlapping ownership and integrating verified results. Ideal for large-scope tasks where parallel processing reduces elapsed time. Decompose tasks into distinct assignments, run scouts in parallel, assign distinct ownership, and synthesize outputs. Keep trivial work with the coordinator to avoid overhead.

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

Coordinates multiple specialized agents via Claude Code's native Agent Tool for complex tasks requiring diverse expertise, such as comprehensive code analysis, feature reviews, and security audits. Enables sequential chains, context passing, and resumable work, with a synthesis protocol for unified recommendations.

Search the public web and verify sources with Parallel's free Search MCP. Use when the user chooses Parallel or its connected tools for current information and URL extraction.

A comprehensive guide and methodology for identifying, measuring, and fixing performance bottlenecks across the entire stack. This skill covers optimizing database queries (e.g., N+1 problems, missing indexes), improving API efficiency (caching, parallel processing), and enhancing frontend performance (memoization, code splitting, image optimization). It emphasizes the critical 'Measure First' principle to ensure all optimizations are data-driven and effective.

Provision enterprise-grade Playwright Java tests with a Page Object Model scaffold, JUnit 5 workflows, thread-safe parallel runs, Allure reporting, CI-friendly setup, and hybrid API/UI coverage to fix flakes and scale browsers.

This skill reviews git diffs or specific file scopes for code reuse, quality, efficiency, clarity, and standards compliance. It optionally applies safe, behavior-preserving fixes. It uses parallel read-only sub-agents to inspect code while the main agent applies changes. Suitable for auditing changes, simplifying code, or refactoring.

Review supervisor, swarm, planner-worker and parallel agent workflows as distributed state machines: task ownership, shared state, branch joins, retries, cancellation, context handoffs, budgets, deadlocks and human escalation before rollout.