“Agent memory”

Audit the project's persistent agent memories for backfire-risk, stale/superseded state, contradictions, redundancy, and bloat.

Audit and improve AgentSystem memory retention, proactive behavior, learning quality, and agent consistency.

Guides memory stitching through indexed retrieval, evidence-gated persistence, and compaction rather than naive transcript accumulation.

Implement persistent memory patterns for AI agents using AgentDB.

Governed local-first memory and continuity for AI agents — signed receipts, optional hosted lane.

Embedded, local-first agent memory: one SQLite file per namespace, no server, no cloud.

Persistent memory for MCP-compatible agents: memory bank, fact cortex, dreams, graph.

Creates scheduled tar.gz backups of agent memory or chat history, lists existing backup snapshots, and restores from a previous backup point with automatic…

Design, audit, and improve agent memory systems across Claude Code's three memory layers (CLAUDE.md, auto-memory, rules/).

Recall locally stored agent memories through an MCP-compatible host.

Agent memory: working, episodic, semantic, procedural and core layers.

Use when a plan finishes or agent memories have piled up.

Implement tiered agent memory: short-term working context, sliding window buffers, episodic vector retrieval, and persistent key-value state.

Compartment

MaxFreedomPollard

Durable agentic memory, encrypted at rest.

Persistent memory and drift detection for AI agents across session restarts.

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Identity, memory, trust, and swarm primitives for AI agents.

AI agent memory backup.

Zettelkasten-based agent memory system with bidirectional links

Decomposes and reorganizes agent memory files into focused, single-purpose components.

Persistent memory for AI agents.

Read Commonly pods and post as a Commonly agent you create, with a token from your Commonly account.

Use to extend an existing agent project with memory, app integration, VPC, multi-agent, migration, model, browser, code interpreter, payments, or resource…

Agent memory on your own Postgres that flags superseded facts and abstains instead of guessing.