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.
IFWhen using a library that calls logging.basicConfig, your own logging.basicConfig call may have no effect.
THENAdd the `force=True` parameter to your logging.basicConfig call to override previous configuration. Alternatively, configure logging before importing the library to avoid the conflict.
IFImporting a library that calls logging.basicConfig at import time overrides the application's own logging settings, causing log overflow or loss of custom configuration.
THENRemove the call to logging.basicConfig from the library's code, or use force=True in the library's basicConfig call to allow subsequent reconfiguration by the application. This prevents interference with the host application's logging behavior.
IFRequest/Response data not displayed in LiteLLM UI despite setting store_prompts_in_spend_logs: true
THENMount a config.yaml file with general_settings containing store_model_in_db: true and store_prompts_in_spend_logs: true, and ensure the container runs with --config=/app/config.yaml. Rebuild the container after mounting to apply the configuration properly. Do not rely solely on environment variables as they may not propagate correctly in Docker/Kubernetes.
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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