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 installing vLLM on macOS (Intel/x86_64), `pip install vllm` fails because it requires torch==2.4.0, which is not available for this platform (PyTorch stopped building macOS x86_64 wheels after torch 2.2.2).
THENOverride the torch version to 2.2.2 (the latest available for macOS x86_64). This can be done by installing torch==2.2.2 before installing vLLM, or by using a dependency override in your project tool (e.g., in PDM, add `[tool.pdm.resolution.overrides]` with `torch = "2.2.2; sys_platform == 'darwin'"`). Note that vLLM may run in CPU-only mode and performance may be limited.
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