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 vellum-memory-v3-migrationgit 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/vellum-memory-v3-migration)<a href="https://agentmods.dev/skills/vellum-ai/vellum-assistant/vellum-memory-v3-migration"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/vellum-memory-v3-migration/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/vellum-memory-v3-migration"><img src="https://agentmods.dev/badge/skills/vellum-ai/vellum-assistant/vellum-memory-v3-migration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Memory Poisoning · line 212 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00063 | $0.05770 |
| Opus 5 | $0.00032 | $0.02885 |
| Sonnet 5 | $0.00013 | $0.01154 |
| Haiku 4.5 | $0.00006 | $0.00577 |
Grade A, and why
vellum-memory-v3-migration 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 4d 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 — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory v3 Migration
Reform an existing memory-v2 corpus into the memory-v3 wiki: a cross-linked set of topical articles where each article's lead is its retrieval card and each ## section is an independently retrievable unit. The assistant is the sole reader and editor of this knowledge base; the goal is a clean, well-organized wiki optimized for retrieval.
This skill is the successor to vellum-memory-v2-migration. That skill backfills an empty corpus from scratch; this one reorganizes a populated one. If concepts/ is empty, stop and run that skill instead.
What actually changes, and why it's two jobs
The mechanical cutover is cheap and mostly automatic: v3 reads the same memory/concepts/*.md tree, the schema is shared, the DB tables already exist, and section embeddings backfill on demand. The work is the reform. v3 retrieval is section-grain: the selector sees a compact card per candidate (the article's lead + its section names), and what reaches context is the best-matching ## section of each selected article in full (the lead when the article was selected without a section match). A section longer than the section index's chunk window (6000 characters, SECTION_CHUNK_CHARS) is indexed, keyed, and injected as independent chunks (Title, Title~1, ...), and the selector may pick any one of them, so a section that should travel as one unit stays under the window. Each injected section is frozen into the conversation once, re-selections point back at it with a one-line pointer, and every resident section is pruned by recency under one byte cap, with no exemptions for any lane. A flat v2 page (bullets, no ## headings, a summary: field v3 ignores) collapses under v3 into one giant lead with no sections: every selection injects the whole page, nothing narrower can match, and that one oversized block crowds the resident budget. So this skill does two things at once:
- Reshape each surviving page into the v3 article skeleton (lead + sections, flat slug,
links:notedges:, optionalcurrent:). - Re-organize the corpus — merge over-fragmented pages into topical articles under hubs, so the wiki is navigable, not a pile of stubs.
What ships with it
4 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.
- 4d ago Changed 6ac0f5bf7161
- 8d ago First seen · 252 lines · 63 tokens per session scan A 5fdb6d11c968
vellum-memory-v3-migration is a skill published in the GitHub repository vellum-ai/vellum-assistant (1,225 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 5,770 once invoked, about $0.0003 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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