embodied-intelligence-skill
Skill0 starsChanged 4 months agoNo licenceView on GitHub
Expert tutor and reference for 具身智能 / embodied intelligence and robot learning, grounded in 《具身智能导论》— the 17-chapter Chinese textbook translated from UC Berkeley CS294-291 "Robots That Learn". Use this skill whenever the user asks about embodied AI / robot learning topics the book covers: 中枢模式发生器(CPG)、 生物运动力学与步态、李群 SO(3)/SE(3) 机器人运动学与动力学、扩散模型/扩散策略 (DDPM, score matching, flow matching, diffusion policy)、灵巧手与欠驱动协同、 触觉感知(GelSight)、运动控制(LQR/MPC/阻抗控制)、卡尔曼滤波与预测控制、视频世界模型、 强化学习(MDP/SAC/PPO/actor-critic)、行为克隆与动作分块、视觉模仿学习(UMI/跨具身)、 足式运动(RMA)、导航(GOAT/可穿越性)、Sim-to-Real 灵巧操作、VLA 与 π0.5 长程规划。 Trigger it for conceptual questions, math derivations, paper explanations, PyTorch implementation help, study/teaching, or "解释一下/推导/这门课/具身智能" requests in this domain — even when the user doesn't name the book. Prefer this skill over answering from memory, because it gives grounded, citable, notation- consistent answers and links to the exact chapter.
In this repository89 other files it gives its agents.
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
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Your trail
Files you open will collect here, so you can find them again.
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.