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.
IFOpensearchVectorStore deletion deletes by internal document ID instead of logical doc_id, causing failed or wrong deletes.
THENReplace the broken `delete_doc_id` call with a custom delete using `self._os_client.delete_by_query` that matches on the `doc_id` field. For Amazon OpenSearch Serverless (AOSS), which does not support `delete_by_query`, implement a workaround such as retrieving the document's internal ID first or using a client-side filter.
IFSupabaseVectorStore.from_documents fails with APIError: invalid input syntax for type bigint when using a table that has a bigint id column, because LangChain v0.0.221+ now generates UUIDs instead of integer IDs.
THENRecreate the Supabase 'documents' table with a uuid primary key instead of bigserial/bigint. Use the following schema: create table documents (id uuid primary key, content text, metadata jsonb, embedding vector(1536) ). Ensure the id column type is uuid and that the table matches the expected schema from the LangChain Supabase integration docs.
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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