MentisDB Agent Memory Graph Database Model Card

这是可索引项目报告证据页：它保留 MentisDB Agent Memory Graph Database 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。

MentisDB Agent Memory Graph Database Model Card

1. Role in Self Evolve

cloudllm-ai/mentisdb is a durable semantic memory engine and versioned skill registry for long-horizon AI agent operation. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.

2. Working Principle

store append-only semantic memory and thought chains in a durable graph substrate -> version skills as integrity-checked artifacts similar to a registry -> retrieve and merge high-signal historical context into active agent decisions -> preserve learning continuity across sessions, models, and team handoffs

3. Evidence Path

web-observed GitHub page showed 71 stars, 8 forks, 641 commits, MIT license, Rust codebase, and explicit durable memory positioning. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.

4. Teaching Use

Use this card to explain Durable Agent Memory Graph Database and Skill Registry Runtime: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.

5. Limits

The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.