Add Vercel logo

Add Vercel

OrganizationPopular
nanocoai
add-vercel

Add Vercel deployment capability to NanoClaw agents. Installs the Vercel CLI in agent containers and sets up OneCLI credential injection for api.vercel.com. Use when the user wants agents to deploy web applications to Vercel.

Overview

Publishernanocoai
Repositorynanoclaw
Skill nameadd-vercel
Stars
30.9K
Forks
12.8K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nanocoai on GitHub. Read the source before you install it.

Installation

Install the Add Vercel AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/add-vercel
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nanocoai/nanoclaw.git /tmp/nanoclaw
mkdir -p .claude/skills
cp -r /tmp/nanoclaw/.claude/skills/add-vercel .claude/skills/add-vercel
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Add Vercel in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Add Vercel on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Add Vercel is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Add Vercel

This skill gives NanoClaw agents the ability to deploy web applications to Vercel. It installs the Vercel CLI in agent containers and configures OneCLI to inject Vercel credentials automatically.

Principle: Do the work — don't tell the user to do it. Only ask for their input when it genuinely requires manual action (pasting a token).

Phase 1: Pre-flight

Check if already applied

Check if the container skill exists:

bash
test -d container/skills/vercel-cli && echo "INSTALLED" || echo "NOT_INSTALLED"

If INSTALLED, skip to Phase 3 (Configure Credentials).

Check prerequisites

Verify OneCLI is working (required for credential injection):

bash
onecli version 2>/dev/null && echo "ONECLI_OK" || echo "ONECLI_MISSING"

If ONECLI_MISSING, tell the user to run /init-onecli first, then retry /add-vercel. Stop here.

Phase 2: Install Container Skill

Copy the bundled container skill into the container skills directory:

bash
rsync -a .claude/skills/add-vercel/container-skills/ container/skills/

Verify:

bash
head -5 container/skills/vercel-cli/SKILL.md

Phase 3: Configure Credentials

Check if Vercel credential already exists

bash
onecli secrets list 2>/dev/null | grep -i vercel

If a Vercel credential already exists, skip to Phase 4.

Set up Vercel API credential

The agent needs a Vercel personal access token. Tell the user:

I need your Vercel personal access token. Go to https://vercel.com/account/tokens and create one with these settings:

  • Token name: nanoclaw (or any name you'll recognize)
  • Scope: "Full Account" — the agent needs to create projects, deploy, and manage domains
  • Expiration: "No expiration" recommended (avoids credential rotation), or pick a date if your security policy requires it

After creating the token, copy it — you'll only see it once.

Once the user provides the token, add it to OneCLI:

bash
onecli secrets create \
  --name "Vercel API Token" \
  --type generic \
  --value "<TOKEN>" \
  --host-pattern "api.vercel.com" \
  --header-name "Authorization" \
  --value-format "Bearer {value}"

Verify:

bash
onecli secrets list | grep -i vercel

Assign the secret to all agents

OneCLI uses selective secret mode — secrets must be explicitly assigned to each agent. Get the Vercel secret ID from the output above, then assign it to every agent:

bash
# set-secrets replaces the entire list — read and merge for each agent.
VERCEL_SECRET_ID=$(onecli secrets list | jq -r '.data[] | select(.name | test("(?i)vercel")) | .id' | head -1)
for agent in $(onecli agents list | jq -r '.data[].id'); do
  CURRENT=$(onecli agents secrets --id "$agent" | jq -r '[.data[]] | join(",")')
  MERGED=$(printf '%s' "$CURRENT,$VERCEL_SECRET_ID" | tr ',' '\n' | sort -u | paste -sd ',' -)
  onecli agents set-secrets --id "$agent" --secret-ids "$MERGED"
done

Phase 4: Ensure Vercel CLI in Container Image

The Vercel CLI is not in the agent image by default — this skill is what adds it. It goes in container/cli-tools.json as a json-merge rather than a Dockerfile edit, which is what keeps the change deterministic and removable.

bash
grep -q '"vercel"' container/cli-tools.json && echo "PRESENT" || echo "MISSING"

If MISSING, append the entry, keeping an exact pinned version — the manifest rejects ranges, so the supply-chain policy still applies:

json
{ "name": "vercel", "version": "52.2.1" }

Then apply it:

bash
./container/build.sh

On an install that builds its own image, that rebuilds it. On one that fetches a published image, the same command adds Vercel as a single layer on top of the image already there, so the publisher's patched components underneath are kept — you are adding a tool, not replacing the runtime. The command says what that does and does not cover.

If PRESENT, the CLI is already in the manifest — skip the rebuild.

Phase 4b: Copy and Run the Dependency Guard

The Vercel CLI is a globally-installed binary — not importable or typed — so a structural test guards the install. Copy it into the host test tree and run it:

bash
cp .claude/skills/add-vercel/vercel-manifest.test.ts src/vercel-manifest.test.ts
pnpm exec vitest run src/vercel-manifest.test.ts

The test asserts both halves of the install: a pinned vercel entry in container/cli-tools.json, and the container skill at container/skills/vercel-cli/. Either alone is a broken install — a manifest entry with no skill leaves the agent a binary nobody told it about, and a skill with no entry tells it to run a command that is not there.

Phase 5: Sync Skills to Running Agent Groups

Container skills are copied once at group creation and not auto-synced. After installing or updating a container skill, sync it to all existing agent groups:

bash
for session_dir in data/v2-sessions/ag-*; do
  if [ -d "$session_dir/.claude-shared/skills" ]; then
    rsync -a container/skills/ "$session_dir/.claude-shared/skills/"
    echo "Synced skills to: $session_dir"
  fi
done

Phase 6: Restart Running Containers

Stop all running agent containers so they pick up the new skills on next wake:

bash
docker ps --filter label=nanoclaw-session -q | xargs -r docker stop

Done

The agent can now deploy web applications to Vercel. Key commands:

  • vercel deploy --yes --prod --token placeholder — deploy to production
  • vercel ls --token placeholder — list deployments
  • vercel whoami --token placeholder — check auth

For the full command reference, the agent has the vercel-cli container skill loaded automatically.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Add Vercel AI skill do?

Add Vercel deployment capability to NanoClaw agents. Installs the Vercel CLI in agent containers and sets up OneCLI credential injection for api.vercel.com. Use when the user wants agents to deploy web applications to Vercel.

Why use Add Vercel on TypingMind?

Because you install it once and use it with any model. Add Vercel is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Add Vercel in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nanocoai/nanoclaw/tree/main/.claude/skills/add-vercel. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Add Vercel?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Add Vercel?

As many as you like. As long as a model supports skills, you can use Add Vercel with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Add Vercel AI skill free?

Yes. It is published on GitHub by nanocoai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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