Skill · em Dados, IA e pesquisa

modal

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.

Procedência

Antes de instalar

13 arquivos · 66,1 KB · só texto, nenhum script

Instalar na sua CLI

O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.

Claude Code

Neste projeto: instala em .claude/skills/modal/.

d=".claude/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.claude/skills/modal/.

d="$HOME/.claude/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Codex

Neste projeto: instala em .agents/skills/modal/.

d=".agents/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.agents/skills/modal/.

d="$HOME/.agents/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Antigravity

Neste projeto: instala em .agents/skills/modal/.

d=".agents/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.gemini/antigravity-cli/skills/modal/.

d="$HOME/.gemini/antigravity-cli/skills/modal"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/modal"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/api_reference.md" "$u/references/api_reference.md" \
  -o "$d/references/examples.md" "$u/references/examples.md" \
  -o "$d/references/functions.md" "$u/references/functions.md" \
  -o "$d/references/getting-started.md" "$u/references/getting-started.md" \
  -o "$d/references/gpu.md" "$u/references/gpu.md" \
  -o "$d/references/images.md" "$u/references/images.md" \
  -o "$d/references/resources.md" "$u/references/resources.md" \
  -o "$d/references/scaling.md" "$u/references/scaling.md" \
  -o "$d/references/scheduled-jobs.md" "$u/references/scheduled-jobs.md" \
  -o "$d/references/secrets.md" "$u/references/secrets.md" \
  -o "$d/references/volumes.md" "$u/references/volumes.md" \
  -o "$d/references/web-endpoints.md" "$u/references/web-endpoints.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Peça ao Rook

Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.modal

Prévia do SKILL.md

---
name: modal
description: 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.
---

# Modal

## Overview

Modal is a serverless platform for running Python code in the cloud with minimal configuration. Execute functions on powerful GPUs, scale automatically to thousands of containers, and pay only for compute used.

Modal is particularly suited for AI/ML workloads, high-performance batch processing, scheduled jobs, GPU inference, and serverless APIs. Sign up for free at https://modal.com and receive $30/month in credits.

## When to Use This Skill

Use Modal for:
- Deploying and serving ML models (LLMs, image generation, embedding models)
- Running GPU-accelerated computation (training, inference, rendering)
- Batch processing large datasets in parallel
- Scheduling compute-intensive jobs (daily data processing, model training)
- Building serverless APIs that need automatic scaling
- Scientific computing requiring distributed compute or specialized hardware

## Authentication and Setup

Modal requires authentication via API token.

### Initial Setup

```bash
# Install Modal
uv uv pip install modal

# Authenticate (opens browser for login)
modal token new
```

This creates a token stored in `~/.modal.toml`. The token authenticates all Modal operations.

### Verify Setup
…

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