Awesome Agent Memory Model Card
这是可索引项目报告证据页：它保留 Awesome Agent Memory 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。
Awesome Agent Memory Model Card
| Field | Value |
|---|---|
| Repository | agentmemoryworld/awesome-agent-memory |
| Category | Agent Memory Resource Survey Index |
| Stars / forks snapshot | 155 / 8 |
| Commits / issues / PRs snapshot | 22 / 1 / 1 |
| Language | Markdown |
| License | Unknown |
| Raw capture | raw-github/agentmemoryworld_awesome-agent-memory.md |
| Updated by | hourly public metadata update, 2026-06-04 16:00 +0800 |
1. Role in Self Evolve
Awesome Agent Memory is an up-to-date survey index for agent-memory papers, systems, and benchmarks rather than a runnable memory runtime. It matters because self-evolving agents need explicit memory, harness, benchmark, and safety substrates before their improvement claims become trustworthy.
2. Working Principle
collect memory papers and systems -> organize them by mechanism and scope -> point readers to benchmark and implementation anchors -> keep the memory landscape navigable as a survey resource
3. Evidence Path
web-observed GitHub page showed 155 stars, 8 forks, 22 commits, 1 issue, 1 pull request, arXiv-backed survey positioning, and no visible license marker on the public repository page. This iteration keeps freshness honest: the snapshot comes from the public GitHub page observed on 2026-06-04, while shell GitHub API access remained blocked in this workspace.
4. Teaching Use
Use this card to explain Agent Memory Resource Survey Index: it shows how survey indexes, embeddable memory SDKs, harness taxonomies, controlled self-modification, or trace-scored benchmarks connect to the broader self-evolving-agent pipeline.
5. Limits
The repository was not cloned in this iteration; no benchmark run, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page signals unless independently revalidated later.