Build multi-step LLM reasoning chains in n8n using Groq, OpenAI, or Claude for structured data extraction, categorization, scoring, and analysis. Use this skill whenever the user wants to chain multiple LLM calls together in an n8n workflow — phrases like "extract entities then categorize", "multi-step LLM prompt", "chain_llm", "LLM pipeline", "classify and score", "entity extraction then enrichment". Also use when processing call transcripts, customer messages, or any unstructured text through multiple analysis passes in n8n. Prefer this pattern over single-shot prompts whenever the output requires both extraction AND reasoning, since single-shot hallucinates categories while chains let each step verify the previous.
Build multi-vendor data enrichment waterfalls in n8n — cascading API calls across SerpAPI, Hunter.io, Apollo, Clearbit, LLM extractors, and scrapers with cost-aware fallbacks. Use this skill whenever the user wants to enrich leads, contacts, companies, or any entity with external data in n8n — phrases like "lead enrichment", "email finder", "data waterfall", "Clay alternative", "find LinkedIn profile", "get company info", "enrich this list of leads". Also use when designing any flow where multiple vendors are tried in sequence until one succeeds. Use this skill before designing such workflows because naive sequential API calls produce $10/lead costs — the waterfall pattern drops that to $0.10 by ordering vendors correctly.
Design production-grade n8n workflows from requirements. Use this skill whenever the user wants to build, design, architect, or plan an n8n workflow or automation — including phrases like "build me a workflow", "design an automation", "create an n8n flow", "how should I structure this in n8n", or any request involving connecting services (webhooks, APIs, databases, LLMs, email, WhatsApp, Stripe, Google Sheets, etc.) through n8n. Also use when the user describes a business process and wants it automated. Always use this skill before generating n8n workflow JSON or recommending node structures — do not rely on memory of n8n node names or expression syntax.
Systematically debug failing n8n workflows — expression errors, node type mismatches, pinned data issues, sub-workflow failures, authentication problems, rate limit errors, and silent data loss. Use this skill whenever the user reports an n8n workflow problem — phrases like "my n8n workflow is failing", "this expression isn't working", "why is this node returning empty", "debug this error", "n8n execution log shows", "workflow runs but no output". Also use when pasted error messages reference n8n concepts (ItemLists, expressions, credentials). Apply this skill before guessing a fix — n8n failures have specific diagnostic patterns, and guessing typically makes the problem worse.
Make n8n workflows idempotent, resumable, and safe at scale using MySQL/Postgres checkpoint tables, batch processing patterns, duplicate prevention, and dynamic table creation. Use this skill whenever the user is building an n8n workflow that processes batches of data, handles webhooks, polls APIs, or runs on a schedule — phrases like "idempotent pipeline", "batch processing", "don't process duplicates", "resumable workflow", "checkpoint", "process 10000 rows", "handle failures gracefully". Also use whenever webhook handlers, ETL jobs, or scraping pipelines are being built. Use this skill proactively — missing checkpoints is the