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.
489 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.
Standardize git remote configuration and issue tracking for contributors working with forked repositories in the libuipc project.
Generate scaffolding for custom Minecraft Bedrock packet analyzers. Includes template code, registration guides, and packet capture workflows.
Real-time observability dashboard for PAI multi-agent activity, featuring live WebSocket streaming, session tracing, and agent workflow debugging.
Home Assistant OS (HAOS) operations skill for agents. Features read-only diagnostics, automation design, health auditing, and safety-first configuration management.
Foundational mental model and operational rules for using TraceMem to ensure secure, auditable, and compliant AI agent execution.
View, filter, and analyze Vocal Bridge voice agent call logs, transcripts, and session details directly from your terminal.
Provides predefined design system references for UI reviews, including Material Design 3, Apple HIG, Tailwind UI, Ant Design, and Shadcn/ui.
Develop, test, sign, and publish governance plugins for Memoria using Rhai or gRPC runtimes. Manage the full plugin lifecycle from scaffolding to activation.
A comprehensive PDF toolkit for extracting text/tables, merging, splitting, rotating, and programmatically generating or filling PDF documents using Python and CLI tools.
Configure and manage Snowflake connections for CLI, Streamlit, and Snowpark environments, including authentication methods like SSO, key pair, OAuth, and profile management.
A systematic, multi-angle web research agent. Use for deep investigation, complex queries, and as a mandatory pre-research step before content generation to ensure evidence-backed, high-quality results.