How long does the integration take?

Change one base URL in an OpenAI-compatible client, or install the Python or TypeScript SDK; the quickstart routes a first request in a few minutes.

Will this lock us into another vendor?

No. The router is Apache-2.0 open source, your provider keys stay yours, and the API is OpenAI-compatible, so leaving is a change of base URL.

What happens when a provider fails?

The router falls back to the next model your policy allows and records the fallback in the trace, so an outage costs a retry, not an incident.

digitalocean-agentic-cloud - Skill

Name: digitalocean-agentic-cloud
Author: bobmatnyc

Imported from bobmatnyc/claude-mpm-skills (toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md). Install upstream with npx skills add bobmatnyc/claude-mpm-skills --skill digitalocean-agentic-cloud. Copyright stays with the author.

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.

Complementary Skills

When using this skill, consider these related skills (if deployed):

digitalocean-storage: Spaces, Volumes, and NFS for datasets.
digitalocean-compute: GPU Droplets or Kubernetes for adjacent workloads.
digitalocean-management: Monitoring and project organization.

Note: Complementary skills are optional. This skill is fully functional without them.

Resources

DigitalOcean Docs:

Gradient AI Agentic Cloud: https://docs.digitalocean.com/products/gradient-ai-agentic-cloud/
Gradient AI Platform: https://docs.digitalocean.com/products/gradient-ai-platform/

Install digitalocean-agentic-cloud and it becomes one more candidate the router can pick - when it fits.

A listing is a routing target with a manifest: what it does, which domains it covers, what it costs and who publishes it. Once installed it sits beside your own models and tools, is scored like any other candidate for each request, and shows up in the trace when it wins. Ratings come from workspaces that installed it, one per account.

{ "ocm": "1", "id": "bobmatnyc-claude-mpm-skills-digitalocean-agentic-cloud", "kind": "skill", "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.", "publisher": "bobmatnyc", "version": "1.0.0", "capabilities": { "domains": [ "coding", "observability" ], "tags": [ "skill-md", "skills-sh" ], "languages": [ "en" ] }, "quality_prior": 0.6, "examples": [ "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." ], "primary": false, "metadata": { "source": { "provider": "skills.sh", "repository": "https://github.com/bobmatnyc/claude-mpm-skills", "path": "toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md", "ref": "HEAD", "url": "https://github.com/bobmatnyc/claude-mpm-skills/blob/HEAD/toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md", "key": "bobmatnyc/claude-mpm-skills/toolchains/platforms/deployment/digitalocean-agentic-cloud/SKILL.md" } }, "instructions": "# DigitalOcean Agentic Cloud Skill\n\n---\nprogressive_disclosure:\n entry_point:\n summary: \"Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents with GPU infrastructure, knowledge bases, and agent routes.\"\n when_to_use:\n - \"When building or deploying AI agents on DigitalOcean\"\n - \"When selecting Gradient AI for GPU-backed inference\"\n - \"When designing agent workflows with knowledge bases and routes\"\n quick_start:\n - \"Choose Gradient AI Agentic Cloud or Gradient AI Platform\"\n - \"Select foundation models and GPU resources\"\n ", "cost": { "context_tokens": 582 } }

digitalocean-agentic-cloud

About

DigitalOcean Agentic Cloud Skill

Overview

Gradient AI Agentic Cloud

Gradient AI Platform

Agent Workflow

Integration Considerations

Complementary Skills

Resources

Install digitalocean-agentic-cloud and it becomes one more candidate the router can pick - when it fits.

What it costs to adopt - in engineering time.

One base URL

No vendor lock-in

Failover built in

Use it

Manifest

Reviews