supermemory
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
426 skills found
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.
A framework for building modular AI agent rigs using Nix, featuring parametrable skills, knowledge management, and automated tool configuration.
Verify Everything Search integration (CLI, HTTP, SDK) for inventory_master to ensure connectivity, service health, and provider availability.
A multi-paradigm ETL pipeline agent supporting batch and streaming data processing, schema inference, and configurable DAG-based transformations for heterogeneous data sources.
Expert code reviewer for Rust projects. Performs comprehensive quality, security, performance, and architectural analysis using Bazel and project-specific conventions.
Advanced multi-language debugging support with stack trace analysis, runtime error triage, and automated diagnostic tools for containerized and distributed systems.
Streamline technical documentation for BattleScope features, maintaining consistency across API, frontend, and architecture layers.
Expert guidance for Claude Messages API: structured outputs, prompt caching, tool use, and migration from deprecated Claude 3.x models to 4.5. Prevents common API errors.
A comprehensive personal life management system using Todoist for task tracking, Logseq for journaling, and AI-driven insights for productivity.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Persistent, semantic long-term memory for AI agents. Save, query, and retrieve cross-session dialogues, decisions, and multimodal context using semantic compression.