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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tool_definition_sanitization
mcp-tool-definition-sani-vertex-ai-returns-400-error-functiondeclaration-pa-e30e6420
IFVertex AI returns 400 error: 'functionDeclaration parameters schema should be of type OBJECT' when LiteLLM proxies tool calls from MCP clients (e.g., Cline) to Gemini models with empty or malformed parameters.
THENEnsure all tool definitions sent to LiteLLM for Gemini/Vertex AI have either 'parameters': None (if no parameters) or 'parameters': {"type":"object","properties":{}} (if parameters are empty). This prevents Vertex AI from rejecting the function declaration.
Tier 170%
tool_definition_sanitization
ai-agents-tool-definition-sani-tool-definitions-with-empty-or-non-object-paramete-fa86c6ea
IFTool definitions with empty or non-OBJECT parameters schema are sent to Vertex AI Gemini, causing 400 BadRequest error.
THENEnsure LiteLLM automatically sanitizes tool definitions for Vertex AI providers: convert empty/missing parameters to {"type": "object", "properties": {}}. As workaround, set `drop_params: true` in model config, or explicitly set `parameters: None` in tool definition. If using v1.80.11, downgrade to v1.80.10.rc.5.
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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