Plugins

2 plugins

Build RAG Pipeline with Pinecone

Build a production RAG pipeline and persistent agent memory using Pinecone as the vector database backend.

6 skills · plugin

Conversational derivation engine — generate agent-native memory architecture from natural conversation. 15 kernel primitives, 26 commands, 17 feature blocks, 3 presets.

10 skills · plugin

Results for “agent-memory”

9 skills

Structured memory system with domains, decay, and links for AI agents, replacing flat memory files with a weighted, interconnected memory palace.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Nemo Rl Session Memory

Maintain durable session memory across agent disconnects by writing structured checkpoints to the repo's session directory, enabling context recovery.

More results

Routes requests into the correct obsidian-mind mode: install, daily session loop, capture, review, maintenance, multi-agent wiring, or semantic search, using a ready-made Obsidian vault template for persistent agent memory.

Persists context across sessions by compiling sources into a local SQLite store and markdown tree, then retrieves relevant memory via embedding search.

Builds a local RAG memory system that indexes session logs and notes into ChromaDB for semantic recall across agent restarts.

Maintains a working memory file for AI agents, tracking active goals, completed tasks, performance metrics, blockers, and key decisions across sessions.

Organizes persistent company memory using a PARA-structured knowledge base with daily notes, atomic facts, and entity tracking for cross-session agent recall.

Maintains a PARA-structured knowledge base on disk for persistent project context, decisions, and architecture records across agent sessions.