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.
IFLLM skips required tool calls in multi-step agentic executions, breaking workflows.
THENUse `prepareStep` to dynamically enforce specific tool calls per step, or `toolChoice` for static control. `prepareStep` can also switch LLM models between steps, preventing tool-skipping behavior.
IFIn multi-step agentic executions, LLMs may skip required tools, leading to incomplete workflows.
THENUse `prepareStep` and `toolChoice` in NeuroLink's GenerateOptions to enforce specific tool calls per step. `prepareStep` allows dynamic per-step logic to change models or enforce tool calls, while `toolChoice` provides static control.
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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