Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
8.3
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0
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DevOps & Infrastructure
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Exceptional skill for serverless Python execution with comprehensive documentation. The SKILL.md provides crystal-clear descriptions of Modal's capabilities for GPU computing, ML deployment, and autoscaling that enable a CLI agent to invoke functions confidently. Task knowledge is outstanding with complete code examples, authentication flows, and common workflows covering ML inference, batch processing, and GPU training. Structure is exemplary: the main document provides a well-organized overview with 9 core capabilities while delegating deep technical details to 11 focused reference files. Novelty is strong—Modal abstracts complex serverless infrastructure, GPU provisioning, and autoscaling that would require extensive cloud configuration and many tokens for a CLI agent to implement manually. The skill meaningfully reduces complexity for deploying ML models and compute-intensive workloads. Minor deduction on novelty only because some simpler Modal tasks could theoretically be handled by a capable agent, though the GPU/ML deployment scenarios provide substantial value. Overall, this is a production-ready skill with excellent documentation quality.
K-Dense-AI
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