twostraws/swiftdata-pro
Writes, reviews, and improves SwiftData code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use SwiftData.
Writes, reviews, and improves SwiftData code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use SwiftData.
npx skills add https://github.com/twostraws/swiftdata-agent-skill/tree/main/skills/swiftdata-proWrites, reviews, and improves SwiftData code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use SwiftData.
Give AI agents their own email inboxes using the AgentMail API. Use when building email agents, sending/receiving emails programmatically, managing inboxes, handling attachments, organizing with labels, creating drafts for human approval, or setting up real-time notifications via webhooks/websockets. Supports multi-tenant isolation with pods.
Your AI agent army, commanded from Slack/Discord/Telegram/Wechat/Lark. Stream Claude Code, OpenCode, or Codex in real-time — from anywhere.
Guide for using Apollo Rover CLI to manage GraphQL schemas and federation. Use this skill when: (1) publishing or fetching subgraph/graph schemas, (2) composing supergraph schemas locally or via GraphOS, (3) running local supergraph development with rover dev, (4) validating schemas with check and lint commands, (5) configuring Rover authentication and environment, (6) exploring or searching a graph's schema for agent-driven discovery (rover schema describe / rover schema search).
Merge the winning agent's branch into base, archive losers, and clean up worktrees. Use when the user runs /hub:merge or asks to land the winning AgentHub result and tidy the session.
React and Vite performance optimization guidelines. Use when writing, reviewing, or optimizing React components built with Vite. Triggers on tasks involving Vite configuration, build optimization, code splitting, lazy loading, HMR, bundle size, or React performance.
Claude Code plugin — sync sessions to Obsidian vaults as structured notes with multi-agent analysis and qmd semantic recall