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Agent skill

Coreweave Deploy Integration

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Deploy inference services on CoreWeave with Helm charts and Kustomize.

MITAuto-check passedDevOps & Cloud

Install Coreweave Deploy Integration

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill coreweave-deploy-integration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace coreweave-deploy-integration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/coreweave-deploy-integration .claude/skills/coreweave-deploy-integration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
coreweave-deploy-integration
GitHub stars
2.8k
Token cost
~1.5k tokens
SKILL.md length
366 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Deploy inference services on CoreWeave with Helm charts and Kustomize.

  • Works in 4 steps: Build → Run → Verify → …
  • Deploying multi-model inference
  • SKILL.md covers Overview, Docker Configuration, Prerequisites and Instructions, plus 8 more sections
  • Calls kubectl, docker and curl; needs COREWEAVE_API_KEY

What it does

Coreweave Deploy Integration is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy inference services on CoreWeave with Helm charts and Kustomize. Use when deploying multi-model inference, managing GPU deployments at scale, or templating CoreWeave manifests. Trigger with phrases like "deploy coreweave", "coreweave helm", "coreweave kustomize", "coreweave deployment patterns".

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Container orchestration and Deployment. It works with Helm and NVIDIA AI Platform. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Deploying multi-model inference
  • Managing GPU deployments at scale
  • Templating CoreWeave manifests
  • With phrases like deploy coreweave

Example prompts

  • “deploy coreweave”
  • “coreweave helm”
  • “coreweave kustomize”
  • “/coreweave-deploy-integration”

Requirements

  • Python 3
  • Docker
  • A credential in COREWEAVE_API_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(helm:*), Bash(kubectl:*), Bash(kustomize:*)

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Build
  2. Run
  3. Verify
  4. Rolling Update

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(helm:*)
    • Bash(kubectl:*)
    • Bash(kustomize:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • kubectl
    • docker
    • curl
    • jq

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.coreweave.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • COREWEAVE_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Coreweave Deploy Integration loads about 1.5k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 366 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 366 words, ~1,474 tokens.

Download SKILL.mdSave it as .claude/skills/coreweave-deploy-integration/SKILL.md (or your agent's skills folder).
name
coreweave-deploy-integration
description
Deploy inference services on CoreWeave with Helm charts and Kustomize. Use when deploying multi-model inference, managing GPU deployments at scale, or templating CoreWeave manifests. Trigger with phrases like "deploy coreweave", "coreweave helm", "coreweave kustomize", "coreweave deployment patterns".
allowed-tools
Read, Write, Edit, Bash(helm:*), Bash(kubectl:*), Bash(kustomize:*)
compatibility
Designed for Claude Code
version
1.11.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, gpu-cloud, kubernetes, inference, coreweave

CoreWeave Deploy Integration

Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.

Overview

Deploy GPU-accelerated inference services on CoreWeave Kubernetes (CKS). This skill covers containerizing inference workloads with NVIDIA CUDA base images, configuring GPU resource limits and node affinity for A100/H100 scheduling, setting up health checks that validate GPU availability and model loading, and executing rolling updates that respect GPU node draining. CoreWeave's scheduler requires explicit GPU resource requests to place pods on the correct hardware tier.

Docker Configuration

Prerequisites

  • A reviewed image digest in an approved registry and a namespace-scoped image pull secret.
  • A production deployment manifest with resource limits, health checks, SLO, and rollback revision.
  • Approval for the target namespace, GPU capacity, and service exposure.

Instructions

  1. Build and scan the image, then deploy the immutable digest to staging first.
  2. Verify readiness, health, GPU allocation, and baseline request behavior before promotion.
  3. Use a controlled rolling update with a timeout and named observer.
  4. Roll back immediately if readiness, error rate, latency, or security verification fails.
dockerfile
FROM nvidia/cuda:12.4.0-runtime-ubuntu22.04 AS base
RUN apt-get update && apt-get install -y --no-install-recommends \
    python3 python3-pip curl && rm -rf /var/lib/apt/lists/*
WORKDIR /app
COPY requirements.txt ./
RUN pip3 install --no-cache-dir -r requirements.txt

FROM base
RUN groupadd -r app && useradd -r -g app app
COPY --chown=app:app src/ ./src/
COPY --chown=app:app models/ ./models/
USER app
EXPOSE 8080
HEALTHCHECK --interval=30s --timeout=10s --retries=3 \
  CMD curl -f http://localhost:8080/health || exit 1
CMD ["python3", "src/server.py"]

Environment Variables

bash
export COREWEAVE_API_KEY="cw_xxxxxxxxxxxx"
export COREWEAVE_NAMESPACE="tenant-my-org"
export MODEL_NAME="meta-llama/Llama-3.1-8B-Instruct"
export GPU_TYPE="A100_PCIE_80GB"
export GPU_COUNT="1"
export LOG_LEVEL="info"
export PORT="8080"

Health Check Endpoint

typescript
import express from 'express';
import { execSync } from 'child_process';

const app = express();

app.get('/health', async (req, res) => {
  try {
    const gpuInfo = execSync('nvidia-smi --query-gpu=name,memory.used --format=csv,noheader').toString().trim();
    const modelLoaded = globalThis.modelReady === true;
    if (!modelLoaded) throw new Error('Model not loaded');
    res.json({ status: 'healthy', gpu: gpuInfo, model: process.env.MODEL_NAME, timestamp: new Date().toISOString() });
  } catch (error) {
    res.status(503).json({ status: 'unhealthy', error: (error as Error).message });
  }
});

Deployment Steps

Step 1: Build
bash
docker build -t registry.coreweave.com/my-org/inference-svc:latest .
docker push registry.coreweave.com/my-org/inference-svc:latest
Step 2: Run
yaml
# k8s/deployment.yaml
resources:
  limits:
    nvidia.com/gpu: 1
    cpu: "4"
    memory: "48Gi"
nodeSelector:
  gpu.nvidia.com/class: A100_PCIE_80GB
bash
kubectl apply -f k8s/deployment.yaml -n tenant-my-org
Step 3: Verify
bash
kubectl get pods -n tenant-my-org -l app=inference-svc
curl -s http://inference-svc.tenant-my-org.svc.cluster.local:8080/health | jq .
Step 4: Rolling Update
bash
kubectl set image deployment/inference-svc \
  inference=registry.coreweave.com/my-org/inference-svc:v2 \
  -n tenant-my-org
kubectl rollout status deployment/inference-svc -n tenant-my-org --timeout=600s
Show full SKILL.md (167 more words)Show less

Error Handling

IssueCauseFix
Pending pod stuckNo GPU nodes available for requested typeCheck kubectl describe node for allocatable GPUs or switch GPU tier
OOMKilledModel exceeds GPU memoryReduce model size, enable quantization, or request larger GPU
nvidia-smi not foundMissing NVIDIA device pluginVerify CoreWeave namespace has GPU operator installed
401 UnauthorizedInvalid API key or expired credentialsRegenerate key in CoreWeave dashboard
Slow rolling updateGPU nodes take time to drainSet terminationGracePeriodSeconds: 300 in deployment spec

Output

  • A versioned, health-checked GPU deployment with declared capacity and ownership.
  • A rollout receipt containing image digest, readiness result, and redacted event evidence.
  • A known rollback command and threshold for using it.

Examples

Deploy an immutable staging image and wait for the rollout before sending traffic:

bash
kubectl -n tenant-staging set image deployment/inference-svc \
  inference=registry.coreweave.com/my-org/inference-svc@sha256:REVIEWED_DIGEST
kubectl -n tenant-staging rollout status deployment/inference-svc --timeout=10m

If the rollout fails, use kubectl rollout undo for the same deployment and record the redacted events. Do not retag latest, bypass health checks, or substitute plaintext credentials.

Resources

Next Steps

See coreweave-webhooks-events.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/.curated/coreweave-deploy-integration of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

Coreweave Deploy Integration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Coreweave Deploy Integration compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Coreweave Deploy Integration this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.5kAutomated safety check: PassMIT
KubeShark for KubernetesLukasNiessen/kubernetes-skill446—~1.2kAutomated safety check: PassMIT
Nim Operator InstallNVIDIA/k8s-nim-operator159—~4.7kAutomated safety check: PassApache-2.0
Release Chartzabbix-community/helm-zabbix132—~1.5kAutomated safety check: PassApache-2.0
Aks Deployment Skilltimothywarner/chatgptclass143—~916Automated safety check: PassCustom licence
Deploy Controllerai-runway/airunway102—~927Automated safety check: PassApache-2.0

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Works with

Categories

Questions about Coreweave Deploy Integration

What does Coreweave Deploy Integration do?

Deploy inference services on CoreWeave with Helm charts and Kustomize. Coreweave Deploy Integration is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy inference services on CoreWeave with Helm charts and Kustomize.

When should I use Coreweave Deploy Integration?

Coreweave Deploy Integration fits situations like: deploying multi-model inference; managing GPU deployments at scale; templating CoreWeave manifests; with phrases like deploy coreweave.

How do I install Coreweave Deploy Integration in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill coreweave-deploy-integration -a claude-code`. Or copy the skill folder (skills/.curated/coreweave-deploy-integration in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/coreweave-deploy-integration in your project. Claude Code loads it when a task matches its description.

How do I install Coreweave Deploy Integration in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill coreweave-deploy-integration -a codex`. Or copy the skill folder (skills/.curated/coreweave-deploy-integration in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/coreweave-deploy-integration in your project. Codex loads it when a task matches its description.

Can I use Coreweave Deploy Integration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill coreweave-deploy-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/coreweave-deploy-integration, .gemini/skills/coreweave-deploy-integration, .github/skills/coreweave-deploy-integration and .opencode/skills/coreweave-deploy-integration in your project.

What does Coreweave Deploy Integration need to run?

Going by SKILL.md and its folder, Coreweave Deploy Integration needs the command-line tools its instructions call (kubectl, docker, curl and jq) and credentials named COREWEAVE_API_KEY. Our summary lists: Python 3; Docker; A credential in COREWEAVE_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(helm:*), Bash(kubectl:*), Bash(kustomize:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Coreweave Deploy Integration access the network?

SKILL.md names 1 domain. As links in the text: docs.coreweave.com. This is read from the text; nothing was executed.

Is Coreweave Deploy Integration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Coreweave Deploy Integration use?

Coreweave Deploy Integration is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Coreweave Deploy Integration use?

About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Coreweave Deploy Integration?

Skills that share tags, products or a category with Coreweave Deploy Integration: KubeShark for Kubernetes (LukasNiessen/kubernetes-skill, 446 stars), Nim Operator Install (NVIDIA/k8s-nim-operator, 159 stars), Release Chart (zabbix-community/helm-zabbix, 132 stars) and Aks Deployment Skill (timothywarner/chatgptclass, 143 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coreweave Deploy Integration?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.