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.
IFSame as above, but user cannot or does not want to downgrade vLLM.
THENChange the role of the existing assistant message from 'assistant' to 'user' and prepend a prefix like '[ASSISTANT message]:' to the content to indicate it was an assistant response. This preserves context while avoiding the bug.
IFUsing vLLM 0.14.0 (or 0.13.0) with GPT-OSS model in multi-turn conversation with existing assistant message and structured output (json_object, grammar, response_schema) causes chat.completions to return null content.
THENDowngrade vLLM to version 0.10.1, which is the version used by the official vLLM Docker image for GPT-OSS. Alternatively, use vLLM 0.11.2 as reported to fix the issue.
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.
Connect a site