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 telegram-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/telegram-setup)<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/telegram-setup"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/telegram-setup.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.02277 |
| Opus 5 | $0.00011 | $0.01138 |
| Sonnet 5 | $0.00004 | $0.00455 |
| Haiku 4.5 | $0.00002 | $0.00228 |
Grade A, and why
telegram-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 5d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are helping your user connect a Telegram bot. The wizard collects the token, the rest of setup runs automatically, and you confirm it worked.
DO NOT use this skill for runtime Telegram operations (sending, replying, reading). That is the separate messaging skill.
What happens without you
Saving the token in the wizard triggers all of this:
| Step | Runs |
|---|---|
Validate the token against getMe |
Automatically, on save |
Store telegram.botId and telegram.botUsername |
Automatically, on save |
| Generate the webhook secret | Automatically, on save |
| Register the platform callback route | Automatically, on save |
Tell Telegram where to send updates (setWebhook) |
Automatically, after the save |
Install the bot commands (setMyCommands) |
Automatically, after the save |
⚠️ CRITICAL: Never run setWebhook, setMyCommands, or assistant webhooks register yourself, and never generate the webhook secret. reconcileTelegramWebhook is idempotent and already runs on the credential change the save produces. Doing it by hand races it, which is how a webhook ends up pointing somewhere stale.
Your job is Steps 1 to 5 below: open the wizard, confirm delivery, link the user's identity.
Step 1: Check existing configuration
⚠️ CRITICAL: If you got here from a wizard-closed notification, or the user just said they finished setup, go straight to Step 3. A successful save leaves both credentials in place, so this step would find them and read it as "already configured" at exactly the moment that means the opposite. Stopping there skips the delivery check and the identity verification, which is the failure this flow exists to prevent.
Otherwise, run assistant credentials list --search telegram (via the bash tool). Note whether bot_token and webhook_secret are present.
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.
- 5d ago First seen · 182 lines · 22 tokens per session scan A d935af91eff3
telegram-setup is a skill published in the GitHub repository vellum-ai/vellum-assistant (1,204 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 2,277 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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