lhl

Agentic Memory

Name: Agentic Memory
Author: lhl

AI community

SOURCE https://github.com/lhl/agentic-memory

Description

Research collection on agent memory architectures, persistence patterns, and output quality maintenance for LLM-based agent systems.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

Agentic Memory Research

Research collection on agent memory architectures, persistence patterns, and output quality maintenance for LLM-based agent systems.

Citation

If you reference this repo’s summaries/analyses in academic or professional work, please cite:

@misc{lin_agentic_memory_2026,
  author       = {Leonard Lin},
  title        = {agentic-memory: Agentic Memory Research Collection (Summaries and Analyses)},
  year         = {2026},
  howpublished = {GitHub repository},
  url          = {https://github.com/lhl/agentic-memory},
}

Reference Summaries

Document	Author	Description
jumperz-agent-memory-stack	@jumperz	31-piece memory architecture split across 3 phases (Core → Reliability → Intelligence). Complete prompt/spec breakdowns for write pipeline, read pipeline, decay, knowledge graph, episodic memory, trust scoring, echo/fizzle feedback loops. The foundational reference that others build on.
joelhooks-adr-0077-memory-system-next-phase	@joelhooks	ADR for joelclaw (personal AI Mac Mini). Maps existing production system (~6 days running, Qdrant 1,343 points) against jumperz's 31 pieces. Plans 3 increments: retrieval quality (score decay, query rewriting), storage quality (dedup, nightly maintenance), feedback loop (echo/fizzle). Includes detailed gap analysis.
coolmanns-openclaw-memory-architecture	coolmanns	12-layer production memory stack for OpenClaw with 14 agents. SQLite+FTS5 knowledge graph (3,108 facts), llama.cpp GPU embeddings (768d, 7ms), three runtime plugins (continuity, stability, graph-memory). 100% recall on 60-query benchmark. Includes activation/decay system, domain RAG, session boot sequences.
drag88-agent-output-degradation

Agentic Memory

Description

Installation

README

Agentic Memory Research

Citation

Reference Summaries

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