Agent Memory Techniques Model Card

这是可索引项目报告证据页：它保留 Agent Memory Techniques Model Card 的源材料入口、机制线索和限制提醒；正文仍需 reader/editor 与 academic public-copy review 后才能当作最终结论引用。

Agent Memory Techniques Model Card

1. Role in Self Evolve

Agent Memory Techniques is a runnable notebook cookbook for 30 LLM-agent memory patterns, covering short-term buffers, long-term stores, cognitive architectures, multi-agent shared memory, framework integrations, LoCoMo-style evaluation and production patterns.

2. Working Principle

memory need -> 30 runnable techniques -> taxonomy/decision tree -> evaluation and production notebooks

3. Evidence Path

web-observed GitHub page showed 412 stars, 58 forks, 4 commits, Apache-2.0 license, Jupyter Notebook/Python/Mermaid stack, 30 runnable notebooks, six memory families, LoCoMo and LongMemEval benchmark coverage, and explicit warnings that the code is educational rather than production-ready; shell GitHub API freshness was blocked.

4. Teaching Use

Use this card to teach memory as a technique taxonomy and hands-on curriculum before treating memory as a self-evolution substrate.

5. Limits

The repository was not cloned in this iteration; no local install, benchmark rerun, security review, skill execution or CI gate was performed. Counts and claims are visible public-page signals unless independently revalidated later.