Self-contained deploy automation — invoke directly, do not decompose. Deploys a Vibes app to Cloudflare Workers via the Deploy API. Use when deploying, publishing, going live, pushing to production, or hosting on the edge.
npx skills add https://github.com/popmechanic/VibesOS --skill cloudflare
> Plan mode: If you are planning work, this entire skill is ONE plan step: "Invoke /vibes:cloudflare". Do not decompose the steps below into separate plan tasks.
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║ ☁️ CLOUDFLARE WORKERS DEPLOY ║
║ Deploy API · Pocket ID · Edge Functions ║
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Deploy your Vibes app to Cloudflare Workers via the Deploy API.
/vibes:vibes or /vibes:factory)No Cloudflare account or wrangler CLI needed — the Deploy API handles infrastructure.
VIBES_ROOT="${CLAUDE_PLUGIN_ROOT:-$(dirname "$(dirname "${CLAUDE_SKILL_DIR}")")}"
bun "$VIBES_ROOT/scripts/deploy-cloudflare.js" --name myapp --file index.html
On first run, a browser window opens for Pocket ID authentication. Tokens are cached for subsequent deploys.
Static Assets: Place images, fonts, or other static files in an assets/ directory next to the app file. The deploy script auto-discovers and includes them (binary files are base64-encoded). Reference in code with absolute paths like /assets/logo.png.
VIBES_ROOT="${CLAUDE_PLUGIN_ROOT:-$(dirname "$(dirname "${CLAUDE_SKILL_DIR}")")}"
bun "$VIBES_ROOT/scripts/deploy-cloudflare.js" --name myapp --file index.html --ai-key "sk-or-v1-your-key"
The --ai-key flag configures the OpenRouter API key for the useAI() hook. Without it, /api/ai/chat returns {"error": "AI not configured"}.
| Endpoint | Method | Description |
|----------|--------|-------------|
| /registry.json | GET | Public registry read |
| /check/:subdomain | GET | Check subdomain availability |
| /claim | POST | Claim a subdomain (auth required) |
| /api/ai/chat | POST | AI proxy to OpenRouter (requires AI key) |
Workers.dev domains only support one subdomain level for SSL. For multi-tenant
apps with subdomains (tenant.myapp.workers.dev), you MUST use a custom domain.
Won't work: tenant.myapp.username.workers.dev (SSL error)
Will work: tenant.myapp.com (with custom domain)
On workers.dev, use the ?subdomain= query parameter for testing:
myapp.username.workers.dev → landing pagemyapp.username.workers.dev?subdomain=tenant → tenant appmyapp.username.workers.dev?subdomain=admin → admin dashboard*, Target: <worker-name>.<username>.workers.dev (Proxied: ON)*.yourdomain.com/*After setup:
yourdomain.com → landing pagetenant.yourdomain.com → tenant appadmin.yourdomain.com → admin dashboard| Problem | Cause | Fix |
|---------|-------|-----|
| Browser doesn't open for auth | Headless environment | Copy the printed URL and open manually |
| Deploy API returns 401 | Expired or invalid token | Delete ~/.vibes/auth.json and retry |
| 404 on subdomain URL | Workers.dev doesn't support nested subdomains | Set up a custom domain (see Custom Domain Setup above) |
| /api/ai/chat returns "AI not configured" | Missing OpenRouter key | Redeploy with --ai-key |
| Stale content after redeploy | Browser cache | Hard refresh (Cmd+Shift+R) or clear cache |
After successful deployment, present these options:
AskUserQuestion:
question: "Your app is deployed! What would you like to do next?"
header: "Next steps"
options:
description: "Configure DNS for subdomain routing (required for multi-tenant)"
description: "Add OpenRouter API key for the useAI() hook"
description: "Transform into SaaS with /vibes:factory, then redeploy"
description: "Visit the deployed URL to verify everything works"
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.
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.
Take popmechanic/cloudflare from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.