Track Embodied AI resources and update foundation documents.
npx skills add https://github.com/kryang03/Notes --skill embodied-ai-resources
Please help me install this Agent Skill. Skill: embodied-ai-resources Source: https://github.com/kryang03/Notes/tree/main/.github/skills/embodied-ai-resources Command: npx skills add https://github.com/kryang03/Notes --skill embodied-ai-resources
具身智能（Embodied AI）领域的资源追踪与知识维护指南，确保 VLA 模型、仿真器、数据集和社区资源等快速演进信息在 EmbodiedAI Foundation 文件中保持时效性。
Audit the EmbodiedAI Foundation page monthly and update VLA models, simulators, and datasets accordingly.
High-intent search queries and answers about installing and using this skill.
Track Embodied AI resources by applying a structured workflow to monitor VLA models, simulators, and datasets. This keeps the EmbodiedAI Foundation documents current with monthly and quarterly governance updates.
Maintain VLA model and dataset links by using a unified resource directory for knowledge management. This supports cross-team version tracking and ensures foundation documents stay synchronized.
Yes, you can audit simulator updates by reviewing the EmbodiedAI Foundation page monthly. The workflow supports tracking performance baselines and deployment status for embodied AI simulators.
No dependencies are required to run the Embodied AI resource tracking workflow. It operates independently to monitor open-source status and update foundation documents with structured frontmatter.
Set up a governance workflow by establishing update cycles and audit records for foundation docs. This enables continuous iteration of VLA models, simulators, datasets, and community resources.
Update Embodied AI dataset entries monthly or quarterly to maintain timeliness. Regular audits ensure the resource directory reflects the latest open-source status and performance baselines.
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