upstash-workflow-js
Build durable, reliable serverless workflows using the Upstash Workflow SDK. Define endpoints, manage complex execution steps, and integrate with QStash for automatic retries and state management.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
165 skills found
Build durable, reliable serverless workflows using the Upstash Workflow SDK. Define endpoints, manage complex execution steps, and integrate with QStash for automatic retries and state management.
Expert guidance for building production-ready Swift database client libraries, covering wire protocols, connection pooling, state machines, and NIO integration.
Complete project architecture and structure guide for LobeHub. Use for codebase exploration, project organization, file location, and architectural context.
Directly interface with RagCode MCP via SSE protocol without complex configuration files or binary dependencies.
Transform AI agents into proactive partners using WAL Protocol, persistent memory buffers, and autonomous cron scheduling to anticipate needs and improve performance.
Control headless Chrome via Cloudflare Browser Rendering using CDP. Capture screenshots, navigate pages, automate scraping, and generate videos in a Cloudflare Workers environment.
Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.
Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.
High-performance in-memory DataFrame library for Python and Rust. Features lazy evaluation, parallel execution, and an Apache Arrow backend for efficient ETL, data processing, and faster pandas alternatives.
Expert skill for Next.js Server Actions, covering form handling, data mutations, revalidation, and optimistic UI updates in the App Router.
Manage database orchestration sessions, state snapshots, and system-level operations for the BAZINGA-DB core engine.
Persistent, semantic long-term memory for AI agents. Save, query, and retrieve cross-session dialogues, decisions, and multimodal context using semantic compression.