菜单
Run the /home/bram/work/quantum_lab Python scripts and demos inside the existing venv ~/.venvs/qiskit. Use when asked (e.g., via Telegram/OpenClaw) to run quant_math_lab.py, qcqi_pure_math_playground.py, quantum_app.py subcommands, quantumapp.server, or notebooks under the repo.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/duclm1x1/Dive-Ai --skill quantum-lab命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
正在显示 SKILL.md
基于 SOC 职业分类
| name | quantum-lab |
| description | Run the /home/bram/work/quantum_lab Python scripts and demos inside the existing venv ~/.venvs/qiskit. Use when asked (e.g., via Telegram/OpenClaw) to run quant_math_lab.py, qcqi_pure_math_playground.py, quantum_app.py subcommands, quantumapp.server, or notebooks under the repo. |
Run quantum_lab repo commands inside the preexisting qiskit venv. Prefer the helper scripts in scripts/ so the venv and repo root are always set.
Use <SKILL_DIR> as the folder where this skill is installed (e.g., ~/clawd/skills/quantum-lab).
bash <SKILL_DIR>/scripts/qexec.sh python quant_math_lab.pybash <SKILL_DIR>/scripts/qexec.sh python qcqi_pure_math_playground.pybash <SKILL_DIR>/scripts/qexec.sh python quantum_app.pybash <SKILL_DIR>/scripts/qexec.sh python quantum_app.py self-testsbash <SKILL_DIR>/scripts/qexec.sh python quantum_app.py playgroundbash <SKILL_DIR>/scripts/qexec.sh python quantum_app.py notebook notebooks/SomeNotebook.ipynbbash <SKILL_DIR>/scripts/qexec.sh python -m quantumapp.server --host 127.0.0.1 --port 8000Use these for quick Telegram/OpenClaw commands. Both gl and ql are supported and equivalent.
bash <SKILL_DIR>/scripts/gl self-testsbash <SKILL_DIR>/scripts/gl playgroundbash <SKILL_DIR>/scripts/gl appbash <SKILL_DIR>/scripts/gl lab-testsbash <SKILL_DIR>/scripts/gl playground-directbash <SKILL_DIR>/scripts/gl notebook notebooks/SomeNotebook.ipynbbash <SKILL_DIR>/scripts/gl web 8000If the user types gl ... or ql ... without a full path, always expand it to the full command:
gl <args> → bash <SKILL_DIR>/scripts/gl <args>ql <args> → bash <SKILL_DIR>/scripts/ql <args>$HOME/work/quantum_lab (override with QUANTUM_LAB_ROOT).~/.venvs/qiskit (override with VENV_PATH).bash <SKILL_DIR>/scripts/qexec.sh pip install -r requirements.txt.