modal-auto-research-skills

Foundational Modal platform knowledge for auto-research agents. Covers app structure, function types, CLI usage, deployment patterns, and development workflow. This skill auto-triggers when code imports `modal` and provides the base layer that the GPU-specific research skills build on.

Interactive GPU sandboxes on Modal with SSH access for debugging, profiling, and prototyping. Launch a container with any GPU (T4 to B200), SSH in, iterate on code with pre-installed ML tools. Use when you need hands-on GPU access for debugging, profiling with nsys/ncu, prototyping training scripts, or testing model serving.

Training apps, experiment patterns, and persistent storage on Modal. Write single-GPU and multi-node training jobs with volumes for data and checkpoints, secrets for W&B/HuggingFace, and fault tolerance via retries and checkpoint auto-resume. Use when you need to run training, fine-tuning, or batch experiments on Modal GPUs.

Parallel Claude Code agent orchestration. Spawn multiple autonomous agents, each with its own GPU or compute, to divide work in parallel. Each agent works independently and reports findings via structured reports; the parent monitors progress and steers agents. Use when you need to run multiple debugging sessions, experiments, or research tasks in parallel across separate GPUs.