Vellum Assistant is a personal AI assistant that remembers information about users, learns their preferences, and takes actions across connected apps. It is intended for people who want an assistant that can manage conversations, unfinished work, and proactive notifications over time. The catalogue skills, hooks, instruction, and setting configure or extend how the assistant works.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vellum-ai/vellum-assistant --skill vercel-token-setupgit clone --depth 1 https://github.com/vellum-ai/vellum-assistantWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vellum-ai/vellum-assistant/vercel-token-setup)<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/vercel-token-setup"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/vercel-token-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/vercel-token-setup"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/vercel-token-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 152 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.02282 |
| Opus 5 | $0.00010 | $0.01141 |
| Sonnet 5 | $0.00004 | $0.00456 |
| Haiku 4.5 | $0.00002 | $0.00228 |
Grade A, and why
vercel-token-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are helping your user set up a Vercel API token so they can publish apps to the web.
Client Check
Determine whether the user has browser automation available (macOS desktop app) or is on a non-interactive channel (Telegram, Slack, etc.).
- macOS desktop app: Follow the Automated Setup path below.
- Telegram or other channel (no browser automation): Follow the Manual Setup for Channels path below.
Path A: Manual Setup for Channels (Telegram, Slack, etc.)
When the user is on Telegram or any non-macOS client, walk them through a text-based setup. No browser automation is used - the user follows links and performs each action manually.
Channel Step 1: Confirm and Explain
Tell the user:
Setting up Vercel API Token
Since I can't automate the browser from here, I'll walk you through each step with direct links. You'll need:
- A Vercel account (free tier works)
- About 2 minutes
Ready to start?
If the user declines, acknowledge and stop.
Channel Step 2: Create the Token
Tell the user:
Step 1: Create an API token
Open this link to go to your Vercel tokens page: https://vercel.com/account/tokens
- Click "Create" (or "Create Token")
- Set the token name to "Vellum Assistant"
- Select scope: "Full Account"
- Set expiration to the longest option available (or "No Expiration" if offered)
- Click "Create Token"
A token value will appear - copy it now, as it's only shown once.
Channel Step 3: Store the Token
Tell the user:
Step 2: Send me the token
Please paste the token value into the secure prompt below.
Present the secure prompt (via the bash tool) — it collects the token through a secure UI and stores it with the right tool policy in one step:
assistant credentials prompt --service vercel --field api_token \
--label "Vercel API Token" \
--placeholder "Enter your Vercel API token" \
--description "Paste the API token you just created on vercel.com" \
--allowed-tools "publish_page,unpublish_page"
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 221 lines · 20 tokens per session scan A 77bb8bc81966
vercel-token-setup is a skill published in the GitHub repository vellum-ai/vellum-assistant (1,214 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 2,282 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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