prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
123 skills found
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Search and reference Chromium documentation, including design docs, APIs, and development guides. Use to locate, browse, or learn about architecture, GPU, network, security, and testing concepts within the Chromium codebase.
Build AI agents, multi-agent systems, and workflows using the OpenAI Agents SDK for TypeScript/JavaScript. Supports tools, handoffs, guardrails, MCP, and realtime voice.
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Retrieve real-time library documentation, code examples, and technical guidance using the Context7 API for frameworks like React, FastAPI, and Next.js.
Advanced web search and reasoning tool for OpenClaw agents. Features citation-heavy synthesis, multi-step reasoning, and live internet access via OpenRouter.
Diagnose and debug Agent-to-Agent (A2A) communication, including orchestrator routing, transport connectivity, agent status, and log analysis for multi-agent systems.
Efficiently search your Zotero library using Python code execution. Enables comprehensive multi-strategy queries, automated deduplication, and relevance ranking without context overflow or system crashes.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Orchestrate parallel Claude Code worker swarms with protocol-based behavioral governance for complex features, multi-step refactors, and long-running autonomous coding sessions.
Local hybrid search engine for markdown notes, documentation, and codebase knowledge bases to reduce token consumption and improve retrieval efficiency.
Verify research idea novelty against recent literature. Use when user says '查新', 'novelty check', or needs to confirm if a method is original.