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Found 11 Skills
Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. **PROACTIVE ACTIVATION**: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. **DETECTION**: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of "agent", "workflow", "agentic", "autonomous". **USE CASES**: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents.
Interactive quiz that maps your AI/ML knowledge to a starting point in the 260-lesson, 20-phase AI Engineering from Scratch curriculum. Trigger phrases: "where should I start", "find my level", "what do I know", "which phase", "assess my knowledge", "placement test", "skip ahead"
Phase quiz for AI Engineering from Scratch. Trigger with "quiz me", "test phase", "check my understanding", "do I know phase 3", or `/check-understanding <phase>`.
Defines the end users as city field-operations workers and guides mobile-first, highly usable task-management UX decisions. OHØJ
Analysis of Lanhu design drafts and Axure prototypes. Directly read prototype pages, design drafts, and slice resources of Lanhu projects via lanhu MCP Server. Trigger scenarios: - Need to obtain Axure prototype pages from Lanhu for requirement analysis - Need to view Lanhu UI design drafts and design parameters - Need to extract slice resources from Lanhu design drafts - Need to collaborate via Lanhu team message board - Need to parse Lanhu invitation links Trigger words: Lanhu, lanhu, design draft, prototype, Lanhu link, design image, slice
Search the web, scrape websites, extract structured data from URLs, and automate browsers using Bright Data's Web MCP. Use when fetching live web content, bypassing blocks/CAPTCHAs, getting product data from Amazon/eBay, social media posts, or when standard requests fail.
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper.
Deterministic AI engineering workflow with multi-agent teams. Triggers: architect mode, consistency sweep, pipeline audit, team workflow
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.
Design composable agentic primitives for flexible workflows. Use when creating reusable workflow building blocks, designing SDLC primitives, or building agent operations that can be combined in different ways.
Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.