ai-brain-learning-memory-pro

ai-brain-learning-memory 的进阶工程版，面向 AI 开发者 / 认知科学爱好者 / agent 架构师。在基础版（概念+例子+速查）之上往工程化推一步：三层记忆的参考实现（Python）、与 agent-memory 工具集成、评测电池 memory_eval_battery.py 的跑法与 6 维解读、OWASP ASI06 记忆投毒防御的代码落地、复习四节点的自动化 rrule 配置、认知科学证据→工程决策映射。建议先读基础版再读本版。触发词：大脑学习记忆进阶、记忆系统实现、memory system design、记忆架构代码、agent-memory 集成、记忆评测电池、记忆投毒防御、ASI06、间隔重复实现、遗忘曲线代码、记忆溯源、reference implementation、学习记忆工程版、brain memory pro。

spec: usk/1.0 interface: type: cli entry_point: scripts/memory_eval_battery.py runtime: python3 call_pattern: args input_schema:

• name: out type: string description: 结果 JSON 输出路径，默认 memory_eval_results.json required: false output_schema: stdout: 六维 0-5 分评测 JSON rc=0 capabilities:
• memory_eval
• benchmark
• llm_memory permissions: network: false filesystem: true subprocess: false requirements: python_packages: [] min_python: "3.8" changelog: "1.0.0: initial upload (USK v3)"

凡自治之物 · LGD 治理学 · 创造术家族 ｜ 评测协议：skill-quality-gate（外部公开评测门禁文档）

English

When to use

When you are building an AI agent's memory subsystem and need production-ready three-tier memory architecture code beyond concept explanations; when your system faces privacy or poisoning risk and needs OWASP ASI06-level defensive code; or when you own the agent's long-term planning and must turn cognitive-science theory into engineering practice including spaced repetition and an automated evaluation battery.

Usage

Run memory_eval_battery.py directly for memory performance evaluation and six-dimension interpretation; consult the built-in code reference for the Python implementation of the three-tier memory structure; and use the OWASP ASI06 defense module for memory-safety hardening scripts.

Process

1. Confirm whether project requirements include memory architecture implementation and safety evaluation metrics.
2. Read the basic-version docs to review core concepts and example comparisons.
3. Set up the environment using the three-tier memory reference implementation or the OWASP ASI06 defense code.
4. Tune memory-module parameters against the agent-memory tool interface.
5. Run memory_eval_battery.py and generate the six-dimension interpretation report.
6. Using the cognitive-science evidence mapping table, turn evaluation results into engineering optimization decisions.

Evidence & safety statement

• Evidence: TBD (no evaluation/badge link yet; fill in the real link here once produced).
• Version: 1.0.1
• Safety: No independent security scan has been done (TBD); the conclusion is pending. No endorsement is given until it is completed.

中文

何时用

当你正在构建 AI Agent 的记忆子系统，需超越概念说明而获取可落地的三层记忆架构代码时；当你的系统面临隐私或投毒风险，需要实施 OWASP ASI06 级别的防御性代码落地方案；或当你负责 Agent 的长期规划，需要将认知科学理论转化为包含间隔重复复述与自动化评测电池的工程实践。

用法

支持直接运行 memory_eval_battery.py 进行记忆性能评估与六维解读输出；可查阅内置代码参考获取三层记忆结构的 Python 实现细节；以及访问 OWASP ASI06 防御模块获取记忆安全加固脚本。

流程

1. 确认项目需求是否包含记忆架构落地与安全评测指标；
2. 运行基础版文档快速回顾核心概念与实例对比；
3. 调用三层记忆参考实现或 OWASP ASI06 防御代码进行环境配置；
4. 根据 agent-memory 工具接口调整内存模块参数；
5. 输入 memory_eval_battery.py 执行测试并生成六维解读报告；
6. 基于认知科学证据映射表，将评测结果转化为工程优化决策。

证据与安全声明

• 证据：TBD（暂无评测/徽章链接；产生后在此更新实际链接）
• 版本：1.0.0
• 安全：未做独立安全扫描（TBD），结论待补；补全前不作推荐背书。