N8n AI workflows scale great… until your system prompt becomes a monster. Anyone using "skills" or modular routing for large AI agents?

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(I used AI to clean up my message because my English is not very good.)

I’ve been loving n8n for building AI-powered workflows — the AI Agent node + tools is super powerful for small-to-medium scale stuff.

Right now my setup uses one big system prompt that configures the agent’s personality, rules, available actions, output format, etc. Works beautifully when the scope is limited.

But as soon as the agent needs to handle more domains (customer support + data analysis + scheduling + content generation + …), the system prompt balloons to thousands of tokens. Every single call pays the full price, even for trivial queries → higher costs, slower responses, harder to maintain/debug.

What I’m dreaming of (and maybe some of you already built):

  • A “skills” system (like Anthropic’s Claude skills / tool-use patterns) where the agent has:

    • A short core prompt (“You are a helpful coordinator…”)

    • A router / classifier that decides which “skill” to activate

    • Only loads/injects the relevant skill instructions (as dynamic context, sub-prompt, or even a separate AI Agent node) for that task

In n8n terms, this could look like:

  • Main AI Agent with minimal prompt + tool-calling to “route to skill X”

  • Or Switch + IF nodes that classify intent first → then call specialized AI Agent sub-workflows with their own focused system prompts

  • Or dynamic prompt injection from a database / GitHub (like the “Use skills in n8n agent node” template)

Has anyone implemented something like this successfully at scale?

  • Multi-agent hierarchies?

  • Intent classification upfront then route to slimmed-down agents?

  • External skill files pulled on-demand?

  • Prompt caching tricks that actually work in n8n?

Would love to see example workflows or patterns — happy to share mine too if it helps spark ideas.

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The AI Agent Tool node is what you want here, it lets your main agent call other agents as tools so each one gets its own focused system prompt and only fires when needed. Way cleaner than trying to route with Switch/IF nodes manually. There’s also a “Use skills in n8n agent node” template on n8n.io that does exactly the skill-loading pattern you described, worth checking out before building from scratch.

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yeah this hits once you go past 2-3 domains.

what worked for me: tiny core prompt (3-4 lines max), domain instructions stored externally, fetched and injected dynamically based on intent. a cheap classifier call upfront to route is way more reliable than one giant agent trying to do everything.

also — structure prompts with stable parts first (persona, format rules), dynamic parts last. both anthropic and openai cache top-down so you get cache hits on the static prefix.