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 sequencesgit 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/sequences)<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/sequences"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/sequences.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 | $0.00010 | $0.00543 |
| Opus 5 | $0.00005 | $0.00271 |
| Sonnet 5 | $0.00002 | $0.00109 |
| Haiku 4.5 | $0.00001 | $0.00054 |
Grade A, and why
sequences 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 9d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an email sequence assistant. Use the sequence tools to help users create and manage automated multi-step email drip campaigns.
Capabilities
Sequence Management
- Create: Build multi-step email sequences with configurable delays, subject lines, body prompts, and per-step approval gates
- List: View all sequences with status and active enrollment counts
- Get: Inspect a sequence's full configuration, steps, and enrollment breakdown
- Update: Modify a sequence's name, description, status, steps, or exit-on-reply behavior
- Delete: Remove a sequence and cancel all its active enrollments
Enrollment
- Enroll: Add one or more contacts (by email) to a sequence, with optional personalization context
- Enrollment List: View enrollments filtered by sequence or status (active, paused, completed, replied, cancelled, failed)
- Import: Bulk-import contacts from a CSV/TSV file into a sequence (preview mode by default, then confirm to enroll)
Lifecycle Control (via sequence_update)
- Pause a sequence: Set
status: "paused"to halt processing of all enrollments - Resume a sequence: Set
status: "active"to resume processing on the next scheduler tick - Pause/resume/cancel an enrollment: Pass
enrollment_id+enrollment_action("pause","resume", or"cancel")
Analytics
- Dashboard: View aggregate metrics across all sequences - total sends, reply rates, completion rates
- Step Funnel: Drill into a specific sequence to see per-step send counts, reach, and drop-off
Usage Notes
- Sequences require a messaging channel (e.g.
"gmail") to be connected before enrollments can be processed. - By default, sequences exit when the contact replies (
exit_on_reply: true). Set tofalsefor sequences that should always complete all steps. - The
sequence_importtool runs in preview mode by default. Call it once to inspect the parsed contacts, then call again withauto_enroll: trueto enroll them. - Step delays are specified in seconds. Use common conversions: 1 hour = 3600, 1 day = 86400, 1 week = 604800.
What ships with it
11 files 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.
- TOOLS.json 9.8 KB
- tools/sequence-analytics.ts 3.5 KB runs code
- tools/sequence-create.ts 1.7 KB runs code
- tools/sequence-delete.ts 736 B runs code
- tools/sequence-enroll.ts 1.7 KB runs code
- tools/sequence-enrollment-list.ts 1.1 KB runs code
- tools/sequence-get.ts 1.6 KB runs code
- tools/sequence-import.ts 3.1 KB runs code
- tools/sequence-list.ts 1009 B runs code
- tools/sequence-update.ts 4.3 KB runs code
- tools/shared.ts 280 B runs code
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.
- 9d ago First seen · 47 lines · 10 tokens per session scan A a9764be6d6f1
sequences is a skill published in the GitHub repository vellum-ai/vellum-assistant (1,204 stars, last pushed today), licensed MIT. It adds 10 tokens to every session and 543 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 2026-08-30.
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