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.
IFLiteLLM 1.82.0 complexity router fails with a Pydantic validation error when clients send message content as a list of parts (e.g., `[{'type':'text','text':'...'}]`) because the type annotation for `PreRoutingHookResponse.messages` is too strict.
THENPatch `litellm/types/router.py`: change `PreRoutingHookResponse.messages` from `List[Dict[str, str]]` to `List[Dict[str, Any]]` and add `Any` to the typing imports.
IFlangfuse's UpdateGenerationBody raises validation errors when usage details contain empty objects or None for integer fields like completion_tokens_details and prompt_tokens_details.
THENBefore passing usage data to langfuse's update method, ensure that nested fields under usageDetails (e.g., completion_tokens_details, prompt_tokens_details) are provided as complete objects with all integer fields set to 0 if empty. For example, if the OpenAI response returns empty `{}` for these details, replace them with a dict containing all expected keys set to 0. Alternatively, check pydantic version compatibility and update the model schema if needed.
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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