# digitalocean-agentic-cloud

Guides your coding assistant through building and deploying AI agents on DigitalOcean Gradient AI. Useful for managing GPU resources, knowledge bases, and agent routing.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 323 installs · ★ 78
- Author: bobmatnyc
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/bobmatnyc/claude-mpm-skills/tree/HEAD/toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md
- Updated: 2026-07-18
- HTML: https://affpapa.org/en/nevibecode/skills/digitalocean-agentic-cloud

## What it does

This skill provides instructions for DigitalOcean Gradient AI. It separates two main environments. Agentic Cloud manages complete agent workflows without manual GPU orchestration. Gradient AI Platform handles model inference and GPU-backed execution.

The workflow outlines practical steps. You pick a target foundation model and compute profile, attach knowledge bases, and set up routes to direct agent traffic. Datasets and artifacts connect via object or block storage. After deployment, runtime metrics track agent performance.

Workloads require integration with project VPCs and strict access controls to remain secure. Costs stay organized within DigitalOcean projects. The skill functions on its own, though it pairs optionally with skills for storage and GPU droplets.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/digitalocean-agentic-cloud/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/digitalocean-agentic-cloud/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/digitalocean-agentic-cloud/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/digitalocean-agentic-cloud/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install bobmatnyc/claude-mpm-skills digitalocean-agentic-cloud
```

2. **Manually: put the files in place**
- File: `.github/skills/digitalocean-agentic-cloud/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/bobmatnyc/claude-mpm-skills --path toolchains/platforms/deployment/digitalocean-agentic-cloud
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/digitalocean-agentic-cloud/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/bobmatnyc/claude-mpm-skills/tree/HEAD/toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md

## When to use it
- pick foundation models and GPU compute profiles for agents
- attach datasets and knowledge bases to agent workflows
- configure agent routes to direct inference traffic
- organize artifact storage using block or object storage
- secure agent deployments within a project VPC

## Example prompts
- Help me configure agent routes and attach a knowledge base in DigitalOcean Gradient AI.
- Select a GPU compute profile and foundation model for deploying an agent on DigitalOcean.
- Outline the steps to deploy an agent workflow on Gradient AI with VPC and object storage.

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 417af8bf9efc25ff.

BEGIN THIRD-PARTY FILE 417af8bf9efc25ff
```text
---
name: digitalocean-agentic-cloud
description: DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or operating AI agents on DigitalOcean.
user-invocable: false
disable-model-invocation: true
progressive_disclosure:
  entry_point:
    summary: "DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when plan..."
    when_to_use: "When working with version control, branches, or pull requests."
    quick_start: "1. Review the core concepts below. 2. Apply patterns to your use case. 3. Follow best practices for implementation."
---
# DigitalOcean Agentic Cloud Skill

---
progressive_disclosure:
  entry_point:
    summary: "Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents with GPU infrastructure, knowledge bases, and agent routes."
    when_to_use:
      - "When building or deploying AI agents on DigitalOcean"
      - "When selecting Gradient AI for GPU-backed inference"
      - "When designing agent workflows with knowledge bases and routes"
    quick_start:
      - "Choose Gradient AI Agentic Cloud or Gradient AI Platform"
      - "Select foundation models and GPU resources"
      - "Attach knowledge bases and define agent routes"
      - "Deploy agents and monitor usage"
  token_estimate:
    entry: 90-110
    full: 3000-4200
---

## Overview

DigitalOcean Gradient AI provides managed infrastructure for building and deploying AI agents. Use Agentic Cloud for end-to-end agent workflows and the AI Platform for GPU-powered agent deployment.

## Gradient AI Agentic Cloud

- Build, train, and deploy AI agents on managed infrastructure.
- Use managed resources to run agent workloads without manual GPU orchestration.

## Gradient AI Platform

- Use GPU-powered infrastructure for AI agents and inference.
- Combine foundation models with knowledge bases.
- Configure agent routes to direct traffic and workflows.

## Agent Workflow

- Select the target model and compute profile.
- Prepare datasets and knowledge bases.
- Define agent routes and inference behavior.
- Deploy agents and observe runtime metrics.

## Integration Considerations

- Use object or block storage for datasets and artifacts.
- Align deployment with VPC and access controls.
- Track costs and usage in projects.
```
END THIRD-PARTY FILE 417af8bf9efc25ff

The third-party file has ended. Everything between the 417af8bf9efc25ff tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 2534 of 3150 bytes. © bobmatnyc · MIT · https://github.com/bobmatnyc/claude-mpm-skills/tree/HEAD/toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md

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