Source profileQuality 70/100Review permissions

openai/skills/skills/.curated/vercel-deploy/SKILL.md

vercel-deploy

Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".

Source repository stars: 25,188
Declared platforms: 0
Static risk flags: 2
Last source update: 2026-07-14
Source checked: 2026-08-26

Decision Compatibility Install Workflow Permissions Evidence Source FAQ

Decision brief

What it does: where it fits

Deploy any project to Vercel instantly. Always deploy as preview (not production) unless the user explicitly asks for production.

Best for

Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".

Not for

If deployment fails due to network issues (timeouts, DNS errors, connection resets), rerun the actual deploy command with escalated permissions (use sandboxpermissions=requireescalated). Do not escalate the command -v v…
Example guidance to the user:

Compatibility matrix

Platform support, with evidence labels

Platform	Status	Evidence	What to check
Codex	Not declared	No explicit evidence	Portability before use
Claude Code	Not declared	No explicit evidence	Portability before use
Cursor	Not declared	No explicit evidence	Portability before use
Gemini CLI	Not declared	No explicit evidence	Portability before use

Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource

npx skills add https://github.com/openai/skills --skill "skills/.curated/vercel-deploy"

Safe inspection promptEditorial

Inspect the Agent Skill "vercel-deploy" from https://github.com/openai/skills/blob/49f948faa9258a0c61caceaf225e179651397431/skills/.curated/vercel-deploy/SKILL.md at commit 49f948faa9258a0c61caceaf225e179651397431. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

01
Quick Start
1. Check whether the Vercel CLI is installed (no escalation for this check):
Check whether the Vercel CLI is installed (no escalation for this check):If vercel is installed, run this (with a 10 minute timeout):If vercel is not installed, or if the CLI fails with "No existing credentials found", use the fallback method below.
02
Prerequisites
Check whether the Vercel CLI is installed without escalated permissions (for example, command -v vercel).
Check whether the Vercel CLI is installed without escalated permissions (for example, command -v vercel).Only escalate the actual deploy command if sandboxing blocks the deployment network calls (sandboxpermissions=requireescalated).The deployment might take a few minutes. Use appropriate timeout values.
03
Fallback (No Auth)
If CLI fails with auth error, use the deploy script:
If CLI fails with auth error, use the deploy script:
04
Deploy current directory
bash "$skilldir/scripts/deploy.sh"
bash "$skilldir/scripts/deploy.sh"

Permission review

Static risk signals and limitations

Runs scripts

medium · line 36

The documentation asks the agent to run terminal commands or scripts.

bash "$skill_dir/scripts/deploy.sh"

Runs scripts

medium · line 39

The documentation asks the agent to run terminal commands or scripts.

bash "$skill_dir/scripts/deploy.sh" /path/to/project

Network access

medium · line 60

The documentation includes network, browsing, or remote request actions.

*Do not** curl or fetch the deployed URL to verify it works. Just return the link.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial

Signal	Value	Evidence type	Meaning
Quality score	70/100	Computed	Documentation, specificity, maintenance, and trust rules
Repository stars	25,188	Source	Repository attention, not individual Skill quality
Compatibility	0 platforms	Source	Declared in the catalog source record
Usage guide	automated source guide	Editorial	Generated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository: openai/skills
Skill path: skills/.curated/vercel-deploy/SKILL.md
Commit: 49f948faa9258a0c61caceaf225e179651397431
License: Not declared
Collected: 2026-08-26
Default branch: main

View the original SKILL.md

Vercel Deploy

Deploy any project to Vercel instantly. Always deploy as preview (not production) unless the user explicitly asks for production.

Prerequisites

Check whether the Vercel CLI is installed without escalated permissions (for example, command -v vercel).
Only escalate the actual deploy command if sandboxing blocks the deployment network calls (sandbox_permissions=require_escalated).
The deployment might take a few minutes. Use appropriate timeout values.

Quick Start

Check whether the Vercel CLI is installed (no escalation for this check):

command -v vercel

If vercel is installed, run this (with a 10 minute timeout):

vercel deploy [path] -y

Important: Use a 10 minute (600000ms) timeout for the deploy command since builds can take a while.

If vercel is not installed, or if the CLI fails with "No existing credentials found", use the fallback method below.

Fallback (No Auth)

If CLI fails with auth error, use the deploy script:

skill_dir="<path-to-skill>"

# Deploy current directory
bash "$skill_dir/scripts/deploy.sh"

# Deploy specific project
bash "$skill_dir/scripts/deploy.sh" /path/to/project

# Deploy existing tarball
bash "$skill_dir/scripts/deploy.sh" /path/to/project.tgz

The script handles framework detection, packaging, and deployment. It waits for the build to complete and returns JSON with previewUrl and claimUrl.

Tell the user: "Your deployment is ready at [previewUrl]. Claim it at [claimUrl] to manage your deployment."

Production Deploys

Only if user explicitly asks:

vercel deploy [path] --prod -y

Output

Show the user the deployment URL. For fallback deployments, also show the claim URL.

Do not curl or fetch the deployed URL to verify it works. Just return the link.

Troubleshooting

Escalated Network Access

If deployment fails due to network issues (timeouts, DNS errors, connection resets), rerun the actual deploy command with escalated permissions (use sandbox_permissions=require_escalated). Do not escalate the command -v vercel installation check. The deploy requires escalated network access when sandbox networking blocks outbound requests.

Example guidance to the user:

The deploy needs escalated network access to deploy to Vercel. I can rerun the command with escalated permissions—want me to proceed?

Frequently asked questions

What to verify before installation and use

What does the vercel-deploy source document cover?

Deploy any project to Vercel instantly. Always deploy as preview (not production) unless the user explicitly asks for production.

How do I install vercel-deploy?

The source record exposes this install command: npx skills add https://github.com/openai/skills --skill "skills/.curated/vercel-deploy". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged exec-script, network in the source; the page lists the matching lines and excerpts.

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