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 completion with response_format returns litellm.JSONSchemaValidationError because the model returns non-JSON text (e.g., markdown summary) instead of the expected JSON schema.
THENSet the environment variable LITELLM_LOCAL_MODEL_COST_MAP=True to use a local model cost map instead of the outdated cloud configuration. If the issue persists, update the system message to explicitly include a hint that the output must be JSON.
IFUsing OllamaFunctions with with_structured_output throws TypeError: Object of type ModelMetaclass is not JSON serializable.
THENUpgrade langchain-experimental to a version including the fix from PR #22339. Until a release is available, install directly from source using `pip install git+https://github.com/langchain-ai/langchain.git#egg=langchain-experimental&subdirectory=libs/experimental`. Alternatively, avoid with_structured_output on OllamaFunctions or use a different LLM that supports structured output correctly.
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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