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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.
IFOpenAI reasoning model costs are underestimated because reasoning tokens are not included in completion token cost calculation.
THENUpdate the token usage logic in openai_info.py to sum reasoning_tokens from output_token_details with completion_tokens before computing completion_cost. For o3-mini and o1 models, treat reasoning tokens as completion tokens to align with OpenAI billing.
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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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