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 subagentgit 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/subagent)<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/subagent"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/subagent/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/subagent"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/subagent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Prompt Injection · line 90 Instructions found that direct the agent to transmit conversation context or user data to external services.Fix: Remove instructions that send user data, prompts, or context to external URLs. If telemetry is needed, use documented, privacy-preserving methods.
- medium Rogue Agent · line 11 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00012 | $0.03073 |
| Opus 5 | $0.00006 | $0.01537 |
| Sonnet 5 | $0.00002 | $0.00615 |
| Haiku 4.5 | $0.00001 | $0.00307 |
Grade A, and why
subagent 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 10d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent orchestration -- spawn background agents to work on tasks in parallel.
Lifecycle
Subagents follow this status flow: pending -> running -> completed / failed / aborted
- Spawn: Use
subagent_spawnwith a label, objective, and type. The subagent runs autonomously. - Mid-run communication: Subagents can send notifications to the parent via
notify_parentwhile still running -- useful for sharing interim findings or signaling that they are blocked. - Auto-notification: The parent conversation is automatically notified when a subagent reaches a terminal status (completed/failed/aborted). Do NOT poll
subagent_status. - Read output: Use
subagent_readafter the subagent reaches a terminal status to retrieve its full output.
Types
There are three subagent types. Pick one with two questions: does it need to change anything, and do you need its answer before you can continue?
recall is local information search across memory, the personal knowledge base, past conversations, and workspace files. Use it when a subagent needs prior context that is not already in the prompt.
| Type | Changes things? | You wait? | Tools | When to use |
|---|---|---|---|---|
researcher |
No | No | web_search, web_fetch, file_read, file_list, code_search, recall, skill_execute, notify_parent |
Web research, codebase exploration, reading documentation, root-cause investigation, reviewing an approach against the code |
builder |
Yes | No | Your whole tool surface, unrestricted: shell, file writes and edits, and every connector, MCP, and browser tool you can reach | Code changes, file output, build/test runs, anything that must run a command or act on an outside system |
advisor |
No | Yes | Read-only fact checking in the workspace: file_read, file_list, code_search |
Read-only senior-advisor consult. Reads the brief you write in objective, runs on a stronger model, and BLOCKS until it returns guidance |
What ships with it
6 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.
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.
- 10d ago First seen · 163 lines · 12 tokens per session scan A f178e78b1f23
subagent is a skill published in the GitHub repository vellum-ai/vellum-assistant (1,214 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 3,073 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.
Other skills, from other repositories
lictor-security-check
Pre-release security audit for ANY project — AI-built or hand-written, web or mobile. Scans the codebase for the full range of real-world risks that get apps breached: leaked API & AI-provider keys, exposed configs/secrets, broken auth & access control (IDOR), injection (SQL/XSS/command), SSRF, open databases & cloud…
lictor-rotate
Walks the user through rotating a leaked API key — step by step, provider-specific. Knows the exact URL to visit, the exact button to click, and how to verify the rotation worked. Supports Stripe, OpenAI, Anthropic, Google Cloud / AI Studio, GitHub, AWS, Slack, Supabase, Firebase, Postmark, and generic OAuth providers.
lictor-explain
Takes any security finding, error message, or jargon-heavy security advice and explains it in plain English. Use this when someone is confused by what /lictor-security-check found, or when they got a security warning from another tool and don't understand it.
lictor-fix-it
Applies the fixes recommended by /lictor-security-check, with the user's explicit permission for each change. Walks through findings one at a time, shows the proposed change, gets approval, applies, runs tests if available, and moves on. Some fixes (rotating leaked credentials) require the user to act outside Claude …
continual-learning
Nightly refinement of an existing per-repo review-style prompt using this reviewer's own finding outcomes. Read confirmed (resolved-by-commit / thumbs-up) and dismissed (thumbs-down) findings, promote the bug patterns the team actually fixes, demote the false-positive patterns, reconcile against the current prompt…
ha-logs
A read-only troubleshooting skill for querying Hope Agent’s local SQLite databases, which store logs, conversations, and background-job status.