419 skills · sorted by relevance
Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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Multi-language Workers development with Rust, Python, and WebAssembly. Use when building Workers in languages other than JavaScript/TypeScript, or when integrating WASM modules for performance-critical code.
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Framework integration for Cloudflare Workers. Use when building with Hono, Remix, Next.js, Astro, SvelteKit, Qwik, or Nuxt on Workers. Covers routing, SSR, static assets, and edge deployment.
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Comprehensive testing guide for Cloudflare Workers using Vitest and @cloudflare/vitest-pool-workers. Use for test setup, binding mocks (D1/KV/R2/DO), integration tests, or encountering test failures, mock errors, coverage issues.
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Cloudflare Workers performance optimization with CPU, memory, caching, bundle size. Use for slow workers, high latency, cold starts, or encountering CPU limits, memory issues, timeout errors.
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Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
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You are an expert in Cloudflare Workers AI, the serverless AI inference platform running on Cloudflare's global network. You help developers run LLMs, embedding models, image generation, speech-to-text, and translation models at the edge with zero cold starts, pay-per-use pricing, and integration with Workers, Pages, and Vectorize — enabling AI features without managing GPU infrastructure.
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Use when running parallel AI workers for any long-running or multi-turn batch API task. Auto-calculates optimal workers + stagger. Supports tiered delegation (V4 Pro orchestrator → V4 Flash workers). 99.95% API success rate at scale.
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Deploy serverless applications on Cloudflare Workers. Covers project setup, JavaScript handler patterns, routing, deployment with Wrangler, and API token configuration. Suitable for APIs, proxies, edge computing, and request transformation.
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Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.
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Cloudflare Workers edge compute platform — Wrangler CLI, KV, D1, R2, Durable Objects, Queues, Workers AI
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Expert debugger for Next.js + Cloudflare Workers + Supabase stacks. Systematic troubleshooting for auth, caching, workers, RLS, CORS, and build issues. Activate on: 'debug', 'not working', 'error', 'broken', '500', '401', '403', 'cache issue', 'RLS', 'CORS'. NOT for: feature development (use language skills), architecture design (use system-architect).
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Cloudflare Workers, KV, Durable Objects, and edge computing development. Use for serverless APIs, caching, rate limiting, real-time features. Activate on "Workers", "KV", "Durable Objects", "wrangler", "edge function", "Cloudflare". NOT for Cloudflare Pages configuration (use deployment docs), DNS management, or general CDN settings.
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Cloudflare Workersのコードを本番運用品質のベストプラクティスに照らして作成・レビューする。新しいWorkerの実装、Workerコードのレビュー、wrangler.jsoncの設定、streaming・floating promises・global state・secrets・bindings・observabilityなどのanti-pattern確認で使用する。事前学習の記憶よりCloudflare公式ドキュメントからの取得を優先する。
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Expert debugger for Next.js + Cloudflare Workers + Supabase stacks. Systematic troubleshooting for auth, caching, workers, RLS, CORS, and build issues. Activate on: 'debug', 'not working', 'error', 'broken', '500', '401', '403', 'cache issue', 'RLS', 'CORS'. NOT for: feature development (use language skills), architecture design (use system-architect).
The English summary is being prepared. Showing the original description.
Cloudflare Workers, KV, Durable Objects, and edge computing development. Use for serverless APIs, caching, rate limiting, real-time features. Activate on "Workers", "KV", "Durable Objects", "wrangler", "edge function", "Cloudflare". NOT for Cloudflare Pages configuration (use deployment docs), DNS management, or general CDN settings.
The English summary is being prepared. Showing the original description.
Delegate feature development, large code refactors, and pull request reviews to Codex, Claude Code, or OpenCode as background workers. Use isolated project checkouts, monitor progress, and arrange completion or failure notifications.
Build Redis caching, request limits, locks that coordinate multiple workers, and messaging. Use concrete implementation patterns to choose data structures, set key expiration, manage connections, and review common production pitfalls.
Coordinate large research or generation tasks across a model team. An orchestrator plans and checks the work, workers execute subtasks in parallel, and an advisor reviews the plan and draft before the results are combined.
Schedule workers to run checks at fixed times while a Claude Code session stays open. Set up recurring security scans, test coverage analysis, or documentation tasks, and find or cancel scheduled jobs.
Coordinates a named team of Codex workers with concrete responsibilities and shared progress records. It selects available collaboration tools, manages communication and separate working copies when needed, and handles integration, team archival, and cleanup after the work ends.
Search and read Slack messages, channels, and threads to catch up on team discussions and decisions. Using the installed CLI and Slack’s official MCP server, it also supports channel posts and replies, with approval required for changes.
Coordinate multiple Claude Code workers through an existing Kanban board. This guide describes task dispatch, automated checks before AI review, per-task cost tracking, human intervention, and recovery after restarts; the runtime and integrations require separate installation.
Move slow Python operations into background jobs so requests can return promptly. Use task queues and workers, the processes that execute queued work, with retry rules, duplicate handling, time limits, and persistent job status.