OpenAgentSkill Registry Manifest
Skill: Agent Memory Techniques
Slug: nirdiamant-agent-memory-techniques
Category: agent-frameworks
Description: Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.

Agent fit:
- Decision: 95/100 Production-ready
- Primary fit: RAG and knowledge
- Role: Primary pick

Supply profile:
- Track: Coding and developer agents
- Scenario: Coding agents
- Applicable agents: Claude Code, OpenAI Agents, LangChain, CLI, Codex
- Maintenance: 10d since push
- Risk: Safe to try

Trust:
- Trust score: 88/100 Production candidate
- Audit: 89/100 Safe to try

Attribution:
- Status: Community indexed
- Source: GitHub star discovery
- Creator: NirDiamant
- Claim URL: https://www.openagentskill.com/skills/nirdiamant-agent-memory-techniques#claim-this-skill

Install:
npx skills add NirDiamant/Agent_Memory_Techniques

URLs:
- Web: https://www.openagentskill.com/skills/nirdiamant-agent-memory-techniques
- API: https://www.openagentskill.com/api/agent/skills/nirdiamant-agent-memory-techniques
- Install API: https://www.openagentskill.com/api/skills/nirdiamant-agent-memory-techniques/install
- Repository: https://github.com/NirDiamant/Agent_Memory_Techniques