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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logging
observability-logging-the-offline-api-does-not-log-prompt-token-ids-maki-e7929ad5
IFThe offline API does not log prompt token IDs, making it hard to debug BOS duplication.
THENAdd logging of preprocessed token IDs (e.g., via logger.info) after preprocessed_inputs in LLMEngine, similar to the online API's logging of prompt_token_ids.
Tier 170%
logging
mcp-logging-using-stdout-e-g-print-console-log-for-logging-in--01226c7e
IFUsing stdout (e.g., print, console.log) for logging in STDIO-based MCP servers corrupts JSON-RPC messages and breaks the server.
THENAlways write logs to stderr instead of stdout. In Python, use print('message', file=sys.stderr) or a logging library that outputs to stderr. In TypeScript, use console.error() or a library that writes to stderr. For HTTP-based servers, stdout logging is safe.
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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