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Agent skill

Coreweave Core Workflow A

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

Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling.

MITAuto-check passedAI & LLM Engineering

Install Coreweave Core Workflow A

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace coreweave-core-workflow-a --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-core-workflow-a .claude/skills/coreweave-core-workflow-a && 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-core-workflow-a
GitHub stars
2.8k
Token cost
~1.2k tokens
SKILL.md length
228 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling.

  • Works in 3 steps: Deploy an InferenceService → Scale-to-Zero Configuration → Test the Endpoint
  • Serving ML models with KServe
  • SKILL.md covers Overview, Prerequisites, Instructions and Error Handling, plus 4 more sections
  • Calls kubectl and curl; needs HUGGING_FACE_HUB_TOKEN

What it does

Coreweave Core Workflow A is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling. Use when serving ML models with KServe, configuring scale-to-zero, or deploying production inference endpoints on CoreWeave. Trigger with phrases like "coreweave inference service", "coreweave kserve", "coreweave model serving", "deploy model on coreweave".

Its SKILL.md is about 1.2k 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 AI & LLM Engineering, covering LLM inference and serving and Machine learning. 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

  • Serving ML models with KServe
  • Configuring scale-to-zero
  • Deploying production inference endpoints on CoreWeave
  • With phrases like coreweave inference service

Example prompts

  • “coreweave inference service”
  • “coreweave kserve”
  • “coreweave model serving”
  • “/coreweave-core-workflow-a”

Requirements

  • A credential in HUGGING_FACE_HUB_TOKEN
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(kubectl:*), Grep

Workflow steps

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

  1. Deploy an InferenceService
  2. Scale-to-Zero Configuration
  3. Test the Endpoint

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(kubectl:*)
    • Grep

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • kubectl
    • curl

    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
    • kserve.github.io

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

  • Credentials

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

    • HUGGING_FACE_HUB_TOKEN

    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 Core Workflow A loads about 1.2k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 228 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

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). 228 words, ~1,228 tokens.

Download SKILL.mdSave it as .claude/skills/coreweave-core-workflow-a/SKILL.md (or your agent's skills folder).
name
coreweave-core-workflow-a
description
Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling. Use when serving ML models with KServe, configuring scale-to-zero, or deploying production inference endpoints on CoreWeave. Trigger with phrases like "coreweave inference service", "coreweave kserve", "coreweave model serving", "deploy model on coreweave".
allowed-tools
Read, Write, Edit, Bash(kubectl:*), Grep
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 Core Workflow: KServe Inference

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

Overview

Deploy production inference services on CoreWeave using KServe InferenceService with GPU scheduling, autoscaling, and scale-to-zero. CKS natively integrates with KServe for serverless GPU inference.

Prerequisites

  • Completed coreweave-install-auth setup
  • KServe available on your CKS cluster
  • Model stored in S3, GCS, or HuggingFace

Instructions

Step 1: Deploy an InferenceService
yaml
# inference-service.yaml
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: llama-inference
  annotations:
    autoscaling.knative.dev/class: "kpa.autoscaling.knative.dev"
    autoscaling.knative.dev/metric: "concurrency"
    autoscaling.knative.dev/target: "1"
    autoscaling.knative.dev/minScale: "1"
    autoscaling.knative.dev/maxScale: "5"
spec:
  predictor:
    minReplicas: 1
    maxReplicas: 5
    containers:
      - name: kserve-container
        image: vllm/vllm-openai:latest
        args:
          - "--model"
          - "meta-llama/Llama-3.1-8B-Instruct"
          - "--port"
          - "8080"
        ports:
          - containerPort: 8080
            protocol: TCP
        resources:
          limits:
            nvidia.com/gpu: "1"
            memory: 48Gi
            cpu: "8"
          requests:
            nvidia.com/gpu: "1"
            memory: 32Gi
            cpu: "4"
        env:
          - name: HUGGING_FACE_HUB_TOKEN
            valueFrom:
              secretKeyRef:
                name: hf-token
                key: token
    affinity:
      nodeAffinity:
        requiredDuringSchedulingIgnoredDuringExecution:
          nodeSelectorTerms:
            - matchExpressions:
                - key: gpu.nvidia.com/class
                  operator: In
                  values: ["A100_PCIE_80GB"]
bash
kubectl apply -f inference-service.yaml
kubectl get inferenceservice llama-inference -w
Step 2: Scale-to-Zero Configuration
yaml
# For dev/staging -- scale down to zero when idle
metadata:
  annotations:
    autoscaling.knative.dev/minScale: "0"    # Scale to zero
    autoscaling.knative.dev/maxScale: "3"
    autoscaling.knative.dev/scaleDownDelay: "5m"
Step 3: Test the Endpoint
bash
# Get inference URL
INFERENCE_URL=$(kubectl get inferenceservice llama-inference \
  -o jsonpath='{.status.url}')

curl -X POST "${INFERENCE_URL}/v1/chat/completions" \
  -H "Content-Type: application/json" \
  -d '{"model": "meta-llama/Llama-3.1-8B-Instruct", "messages": [{"role": "user", "content": "Hello!"}]}'

Error Handling

ErrorCauseSolution
InferenceService not readyGPU not availableCheck node capacity and affinity
Scale-to-zero cold startFirst request after idleSet minScale: 1 for production
Model loading timeoutLarge model downloadPre-cache model in PVC
OOMKilledModel too largeUse multi-GPU or quantized model

Output

  • A namespace-scoped inference service with declared compute, GPU, and secret inputs.
  • A readiness and endpoint smoke-test result suitable for the deployment record.
  • A scale-to-zero configuration limited to appropriate non-production workloads, with a documented production availability decision.

Examples

Deploy to staging and wait for the service readiness condition before sending a minimal health request:

bash
kubectl -n inference-staging apply -f inference-service.yaml
kubectl -n inference-staging get inferenceservice llama-inference --watch
kubectl -n inference-staging get pods -l serving.kserve.io/inferenceservice=llama-inference

If readiness stalls, inspect events, image pull status, GPU availability, and the secret reference. Do not expose the endpoint publicly or replace a secret reference with a plaintext token as a debugging shortcut.

Resources

Next Steps

For GPU training workloads, see coreweave-core-workflow-b.

© 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-core-workflow-a of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

Coreweave Core Workflow A 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 Core Workflow A compared with similar skills
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Coreweave Core Workflow A this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.2kAutomated safety check: PassMIT
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Databricks ML Trainingdatabricks/databricks-agent-skills345—~4.6kAutomated safety check: PassCustom licence
ML Research LabAnastasiyaW/codex-claude-code-config154—~794Automated safety check: PassMIT
Ais Benchascend-ai-coding/awesome-ascend-skills174—~2.7kAutomated safety check: PassNone
Cookbook Aimldatabricks-solutions/databricks-apps-cookbook183—~1.7kAutomated safety check: PassCustom licence

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Categories

Questions about Coreweave Core Workflow A

What does Coreweave Core Workflow A do?

Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling. Coreweave Core Workflow A is an agent skill from jeremylongshore/tons-of-skills-marketplace. Deploy KServe InferenceService on CoreWeave with autoscaling and GPU scheduling.

When should I use Coreweave Core Workflow A?

Coreweave Core Workflow A fits situations like: serving ML models with KServe; configuring scale-to-zero; deploying production inference endpoints on CoreWeave; with phrases like coreweave inference service.

How do I install Coreweave Core Workflow A in Claude Code?

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

How do I install Coreweave Core Workflow A in Codex?

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

Can I use Coreweave Core Workflow A 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-core-workflow-a -a cursor` (or -a -a, -a or -a for the others). To copy it by hand, put the folder in .cursor/skills/coreweave-core-workflow-a, .gemini/skills/coreweave-core-workflow-a, .github/skills/coreweave-core-workflow-a and .opencode/skills/coreweave-core-workflow-a in your project.

What does Coreweave Core Workflow A need to run?

Going by SKILL.md and its folder, Coreweave Core Workflow A needs the command-line tools its instructions call (kubectl and curl) and credentials named HUGGING_FACE_HUB_TOKEN. Our summary lists: A credential in HUGGING_FACE_HUB_TOKEN. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(kubectl:*), Grep. Compatibility (from SKILL.md): Designed for Claude Code.

Does Coreweave Core Workflow A access the network?

SKILL.md names 2 domains. As links in the text: docs.coreweave.com and kserve.github.io. This is read from the text; nothing was executed.

Is Coreweave Core Workflow A 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 Core Workflow A use?

Coreweave Core Workflow A 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 Core Workflow A use?

About 1.2k tokens (SKILL.md is roughly 4.9k 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 Core Workflow A?

Skills that share tags, products or a category with Coreweave Core Workflow A: ML Engineer (davila7/claude-code-templates, 33k stars), Databricks ML Training (databricks/databricks-agent-skills, 345 stars), ML Research Lab (AnastasiyaW/codex-claude-code-config, 154 stars) and Ais Bench (ascend-ai-coding/awesome-ascend-skills, 174 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coreweave Core Workflow A?

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.