← 返回 Skills 市场
dustin-a11y

Quantum Agent Memory

作者 Dustin-a11y · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
96
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install quantum-agent-memory
功能描述
QAOA-powered memory optimization for AI agents. Uses quantum computing (Qiskit) to solve three memory management problems: clustering related memories, selec...
安全使用建议
Before installing or running this skill: 1) Treat the manifest omissions as suspicious — the code requires QUANTUM_API_TOKEN, MEM0_URL, and an IBM quantum token even though the registry lists none. 2) Do not run the example systemd service as root; prefer a dedicated unprivileged system user. 3) Inspect and possibly edit hard-coded paths in scripts/ibm_cron.py (RESULTS_DIR, TOKEN_FILE) before running. 4) Understand that the OpenClaw plugin injects selected memories into every agent prompt — review and control which agents the plugin is enabled for. 5) Be aware QiskitRuntimeService.save_account will persist IBM credentials to local config; store tokens with least privilege and in a controlled location. 6) If you want to proceed, run the service in an isolated environment (container or dedicated VM), lock down MEM0 and API tokens, and review plugin files that will be placed into agent extension directories.
功能分析
Type: OpenClaw Skill Name: quantum-agent-memory Version: 1.0.0 The skill bundle implements a complex quantum-based memory management system using QAOA, but contains several high-risk security practices. Specifically, the documentation in 'references/api-setup.md' provides a systemd service template that runs the API server as 'root', and 'scripts/ibm_cron.py' contains hardcoded absolute paths ('/home/dt/...') and directly accesses sensitive credentials in the user's home directory ('~/.ibm_quantum_token'). While the code appears to perform its stated function, these vulnerabilities and the lack of environment sanitization pose a risk of privilege escalation and credential exposure.
能力标签
cryptorequires-oauth-token
能力评估
Purpose & Capability
The name/description (QAOA memory optimization) matches the included code and docs: FastAPI endpoints, QAOA circuits, and Mem0 integration. However the registry metadata lists no required env vars or credentials while the README and code clearly require QUANTUM_API_TOKEN, MEM0_URL, and an IBM quantum token – an inconsistency between declared requirements and actual needs.
Instruction Scope
Runtime instructions and code call out to a local Mem0 API, will fetch/store agent memories, and instruct installing an OpenClaw plugin that hooks into before_prompt_build (injecting memories into every agent prompt). The scripts also perform filesystem operations (write results, read ~/.ibm_quantum_token) and recommend running a systemd service as root. These actions are within the stated purpose but are broad in scope (affect all agents) and include hard-coded paths and fallback behavior that were not declared in registry metadata.
Install Mechanism
There is no packaged installer (instruction-only). The SKILL.md instructs creating a venv and pip-installing qiskit, FastAPI, etc., which is expected for this project. Risk is moderate because installing qiskit and qiskit-ibm-runtime pulls heavy dependencies, but there is no download-from-untrusted-URL or opaque binary installer in the manifest.
Credentials
The registry claims no required env vars, yet the code/docs use QUANTUM_API_TOKEN (API auth), MEM0_URL, and IBM_QUANTUM_TOKEN (or ~/.ibm_quantum_token). The IBM token is saved via QiskitRuntimeService.save_account (persisting credentials). Requiring an API token to allow the plugin to access or inject all agent memories is proportionate to the feature but should have been declared; omission is a red flag.
Persistence & Privilege
The integration model installs an agent plugin that runs on before_prompt_build and injects memories into every agent's prompt — this gives the skill-wide reach across agents on the host. The SKILL.md also recommends running the API as a systemd service (example shows User=root). The skill does not set always:true, but the suggested deployment (plugin + systemd as root) creates persistent, high‑privilege presence if followed.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install quantum-agent-memory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /quantum-agent-memory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
- Initial release of quantum-agent-memory. - Implements QAOA-powered memory management for AI agents, replacing classical heuristics for clustering, compaction, and recall. - Supports integration with Mem0 and OpenClaw plugins. - Allows benchmarking and submission of circuits to IBM Quantum hardware. - Provides a FastAPI server for live agent integration and API endpoints. - Includes technical references for setup, systemd, and a whitepaper.
元数据
Slug quantum-agent-memory
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Quantum Agent Memory 是什么?

QAOA-powered memory optimization for AI agents. Uses quantum computing (Qiskit) to solve three memory management problems: clustering related memories, selec... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 96 次。

如何安装 Quantum Agent Memory?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install quantum-agent-memory」即可一键安装,无需额外配置。

Quantum Agent Memory 是免费的吗?

是的,Quantum Agent Memory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Quantum Agent Memory 支持哪些平台?

Quantum Agent Memory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Quantum Agent Memory?

由 Dustin-a11y(@dustin-a11y)开发并维护,当前版本 v1.0.0。

💬 留言讨论