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.
IFAI model returns inconsistent or poorly formatted responses when given a single user prompt without prior examples.
THENInclude few-shot examples in the messages array by providing a sample user query and the desired assistant response before the actual user query. This guides the model to follow the expected format and improves response consistency. For instance, after a system prompt, add a user message with an example query and an assistant message with the ideal response, then the real user message.
IFOpenAI-compatible chat completions response contains a leading space in the generated assistant content.
THENTrim any leading whitespace from the generated output before returning it in the response. Apply lstrip() to the decoded token string after generation to remove unintended spaces. Additionally, verify that the tokenizer or sampling process does not insert a leading space token; if so, skip or suppress that token.
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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