ai-patternslisted

# AI Patterns ## Detected <!-- Populated by scan during init. Do not edit manually. --> ## Rules - All LLM calls through a centralized client wrapper. Configure retry, timeout, and error handling once — not per-call. - Never interpolate raw user input into system prompts. User content goes in user messages with clear role boundaries. System instructions stay immutable. - Treat all LLM output as untrusted. Validate and sanitize before using in database queries, HTML rendering, or business logic. - Handle LLM errors by type: retry rate limits with backoff, truncate input for context overflow, log content filter triggers, fail gracefully for API outages. - Use structured output (JSON mode, tool_use) for data extraction. Never regex-parse free-text LLM responses for application data. - Centralize prompt templates — don't scatter prompt strings across business logic. Prompts should be versionable, testable, and reviewable independently. - Log model, token count, and latency per LLM call. You can't optimize cost or debug quality without knowing what each request consumed. ## Gotchas *Not yet captured. Add as you discover them during development.* ## Examples *Not yet captured. Add short snippets showing the RIGHT way.*