## Description: <br>
Agent Memory System v12 provides structured long-term memory for AI agents with five-way retrieval, dual timelines, causal chains, proactive memory management, resilient configuration, circuit breakers, and GDPR-oriented controls. <br>

This skill is ready for commercial/non-commercial use. <br>

## Publisher: <br>
[concisegjh](https://clawhub.ai/user/concisegjh) <br>

### License/Terms of Use: <br>
MIT-0 <br>


## Use Case: <br>
Developers and agent builders use this skill to add persistent local or self-hosted memory to AI agents, including storing, recalling, pruning, exporting, and auditing memories through SDK, CLI, REST, and MCP-style interfaces. <br>

### Deployment Geography for Use: <br>
Global <br>

## Known Risks and Mitigations: <br>
Risk: Persistent long-term memory can store sensitive personal, credential, or regulated information. <br>
Mitigation: Keep the database local by default, enable available privacy controls, and verify delete/export behavior before storing sensitive or regulated data. <br>
Risk: Optional server, MCP HTTP, export, and maintenance surfaces can expose or modify memory data if deployed without strong access controls. <br>
Mitigation: Bind services to localhost unless intentionally exposed, set strong API keys before server use, and require explicit user approval for high-impact operations. <br>
Risk: Remote model provider configuration can send memory content outside the local environment. <br>
Mitigation: Use trusted provider URLs and API keys only, avoid untrusted OPENAI_BASE_URL, LITELM_API_BASE, or MIMO_API_URL values, and process only consented data. <br>
Risk: Retrieved memories may be inaccurate or untrusted context for an agent. <br>
Mitigation: Treat recall results as user context rather than instructions, review retrieved memories periodically, and remove incorrect or suspicious entries. <br>


## Reference(s): <br>
- [ClawHub skill page](https://clawhub.ai/concisegjh/super-memory) <br>
- [Project homepage](https://github.com/agent-memory/agent-memory) <br>
- [API reference](docs/API_REFERENCE.md) <br>
- [SDK quickstart](docs/SDK_QUICKSTART.md) <br>
- [Runbook](RUNBOOK.md) <br>
- [BAAI bge-small-zh-v1.5 model](https://huggingface.co/BAAI/bge-small-zh-v1.5) <br>
- [sqlite-vec package](https://pypi.org/project/sqlite-vec/) <br>
- [sentence-transformers package](https://pypi.org/project/sentence-transformers/) <br>
- [FlagEmbedding package](https://pypi.org/project/FlagEmbedding/) <br>


## Skill Output: <br>
**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance] <br>
**Output Format:** [Markdown guidance with Python, bash, and API examples; runtime outputs include text memory context and JSON-like API results] <br>
**Output Parameters:** [1D] <br>
**Other Properties Related to Output:** [Uses persistent local storage by default and may use optional server, MCP, embedding, LLM, or web API surfaces when configured.] <br>

## Skill Version(s): <br>
12.1.0 (source: ClawHub release metadata and SKILL.md frontmatter) <br>

## Ethical Considerations: <br>
Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>
