Pattern preview · 12 of 4,089 sample rules shown · site-specific intelligence stays private
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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.
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Tier-2 (your patterns)
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persistent_memory
observability-persistent-memory-llm-agents-lose-context-across-runs-no-memory-of-p-2a3b3c01
IFLLM site_1 lose context across runs; no memory of past decisions or outcomes.
THENImplement a persistent decision log by appending each completed run's decision to a markdown file (default: ~/.tradingagents/memory/trading_memory.md). On the next run for the same ticker, fetch realized return (raw and alpha vs SPY), generate a one-paragraph reflection, and inject most recent same-ticker decisions plus recent cross-ticker lessons into the Portfolio Manager prompt. Can customize the log path via TRADINGAGENTS_MEMORY_LOG_PATH.
Tier 170%
persistent_memory
mcp-persistent-memory-need-to-remember-user-information-across-chat-sess-e48abb71
IFNeed to remember user information across chat sessions to personalize interactions and maintain context.
THENImplement a persistent memory MCP server using a local knowledge graph. Define entities with unique names, types, and atomic observations. Create relations in active voice to connect entities. Provide tools for CRUD operations: create_entities, create_relations, add_observations, delete_entities, delete_observations, delete_relations, read_graph, search_nodes, open_nodes. Use a JSONL file for storage, configurable via MEMORY_FILE_PATH environment variable.
Tier 170%
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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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