
Supermemory is a state-of-the-art memory and context infrastructure for AI agents. Use this skill when building applications that need persistent memory, user personalization, long-term context retention, or semantic search across knowledge bases. It provides Memory API for learned user context, User Profiles for static/dynamic facts, and RAG for semantic search. Perfect for chatbots, assistants, and knowledge-intensive applications.
Search your coding memory. Use when user asks about past work, previous sessions, how something was implemented, what they worked on before, or wants to recall information from earlier sessions.
Save important project knowledge to memory. Use when user wants to preserve architectural decisions, significant bug fixes, design patterns, or important implementation details for team reference.
Search your coding memory. Use when user asks about past work, previous sessions, how something was implemented, what they worked on before, or wants to recall information from earlier sessions.
Save important project knowledge to memory. Use when user wants to preserve architectural decisions, significant bug fixes, design patterns, or important implementation details for team reference.
Automatically benchmark your custom memory implementation against established systems like Supermemory. Set up a public benchmark, or create your own. Compare solutions against quality, latency, features and cost, easily, with a simple UI and CLI.
Search persistent memory for relevant information from past coding sessions. Use when user asks about previous work, past bugs, architectural decisions, or anything that may have been worked on before.
Deep codebase exploration to initialize project memory. Use when starting work on a new project or when user asks to "index" or "learn" the codebase.
Save important information to persistent memory. Use when user explicitly asks to remember something, or when you've solved a significant problem worth preserving.