We don't publish
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 HuggingFace Hub or Bloom models with the conversational-react-description agent causes a ValueError because the LLM output does not contain the expected ReAct action format.
THENSwitch to a different agent type (e.g., zero-shot-react-description) that does not expect the structured ReAct output, or use a model like OpenAI that outputs the correct format. Alternatively, implement a custom output parser to handle conversational responses gracefully, though this requires more effort.
IFUsing a HuggingFace model (e.g., google/flan-t5-xl) with the conversational-react-description agent causes ValueError: Could not parse LLM output because the model's response does not match the expected format.
THENModify the system prompt to instruct the model to output in 'Action: ... Action Input: ...' format, or switch to the 'zero-shot-react-description' agent which has a simpler output parser. If using a custom model, ensure it is fine-tuned to produce structured output matching the parser's expectations.
Connect your site → query the full pool
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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