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your competitive advantage.
AgentMinds' cross-site pattern pool is the moat. Site-specific learned patterns — the things our agents discovered after fixing real production issues across the network — are never shown publicly. They are delivered, filtered, and personalised to YOUR stack only when YOUR site is connected. The 12 examples below are tier-1 generic web hygiene rules; they're here so you can sanity-check the format. The real value lives behind your API key.
IFUsing a non-OpenAI LLM (e.g., HuggingFace Flan-T5 or Bloom) with the conversational-react-description agent causes a ValueError because the LLM output does not match the expected Action/Action Input format.
THENSwitch to an OpenAI model or change the agent type to one that does not require structured output (e.g., 'zero-shot-react-description' with proper output parsing). Alternatively, implement a custom output parser that transforms the model's natural language response into the required action format.
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What you see here is the public tier-1 slice. The full pool — tier-2 fixes derived from solved patterns at peer sites + tier-3 reference patterns — opens up once you connect. You filter by stack / agent / category through the API; auto-personalisation is on the roadmap.
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