Geo Fundamentals
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
Migrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved…
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vellum-ai/vellum-assistant assistant-migration --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/assistant-migration .claude/skills/assistant-migration && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .claude/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migrationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vellum-ai/vellum-assistant assistant-migration --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/assistant-migration .agents/skills/assistant-migration && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .agents/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vellum-ai/vellum-assistant assistant-migration --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/assistant-migration .cursor/skills/assistant-migration && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .cursor/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vellum-ai/vellum-assistant.git --path skills/assistant-migration--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vellum-ai/vellum-assistant assistant-migration --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/assistant-migration .gemini/skills/assistant-migration && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .gemini/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vellum-ai/vellum-assistant assistant-migrationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/assistant-migration .github/skills/assistant-migration && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .github/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vellum-ai/vellum-assistant assistant-migration --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/assistant-migration .opencode/skills/assistant-migration && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "assistant-migration" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/skills/assistant-migration into .opencode/skills/assistant-migration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "assistant-migration", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
assistant-migrationMigrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved…
Assistant Migration is an agent skill from vellum-ai/vellum-assistant. Migrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved memories, tools, GPTs, workflows, integrations, and relationships, then mapping as much as safely possible into Vellum primitives. Handles single-source and multi-source migrations with a unified, deduplicated inventory.
Its SKILL.md is about 6.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 12 other files, including scripts and reference files (for example `references/README.md`, `references/chatgpt.md` and `references/claude.md`). Compatibility notes: Designed for Vellum personal assistants
It works with OpenAI. The repository describes itself as: An AI Assistant that’s easy to setup, does your work 24/7, knows your preferences and gets better over time. The licence is MIT.
10 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 844117a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 4 files in scripts/ (TypeScript), which the agent can run.
Shell commands in SKILL.md call:
bunFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Vellum personal assistants
From compatibility in the SKILL.md frontmatter.
Assistant Migration loads about 6.3k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 110 tokens; SKILL.md has 2,634 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from vellum-ai/vellum-assistant at commit 844117a, republished under its MIT licence (© vellum-ai). 2,634 words, ~6,265 tokens.
.claude/skills/assistant-migration/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.Help the creator migrate from another AI assistant into Vellum. Preserve as much of the source assistant as can be understood safely. Non-Vellum systems (OpenClaw, Hermes, Manus, and others) evolve quickly, so never assume their internals follow a fixed schema: inspect the actual source artifacts in front of you and map them into Vellum primitives. The bundled memory parsers in scripts/ follow the same rule; they introspect whatever artifact they are given instead of hardcoding a layout, and everything they emit is a review candidate, never a finished import.
scripts/: they avoid schema assumptions by design (ZIP entries matched by name/content heuristics, SQLite tables discovered via sqlite_master introspection) and their output always goes through creator review before anything is saved.The creator may not know where their other assistant stores its internals. Help them find the safest available source of truth before asking them to upload or paste data.
Start with low-risk discovery:
When internals are hard to access, fall back to an interview-style migration: ask the creator and source assistant for high-signal summaries, then rebuild in Vellum with review.
Before copying large folders or attachments, estimate source size and check available space in the current Vellum workspace. Use available storage diagnostics or shell filesystem probes when available, migrate large assets in batches, and pause for the creator if the import could crowd the workspace or trigger disk-pressure cleanup.
Once the source assistant is identified, consult the matching reference for the exact data-directory layout, a bundling recipe with explicit --exclude flags for secret-bearing paths, and the after-import rebind checklist:
For ChatGPT conversation history specifically, do not parse export ZIPs here — invoke the chatgpt-import skill, which owns the export-and-parse flow. The ChatGPT reference covers only the non-conversation material (custom instructions, saved memories, GPT configs).
These are reconnaissance notes, not adapters. They tell you where to look and what to leave behind. The preferred flow is a single tar archive that the creator uploads to the conversation as a chat attachment. Never run curl, wget, or any other fetcher against a URL the creator pastes in chat — a chat-supplied URL substituted into a shell command is a confused-deputy surface (shell substitution inside double quotes, SSRF against private networks, and a bypass of the platform's structured URL-safety checks). See references/README.md for the shared tar-and-transport model and the rules each per-assistant reference must follow.
Ask only for missing essentials:
If the user already provided enough context, start inspecting.
Build an inventory grouped by Vellum primitive. For each candidate item, capture:
Do not mutate Vellum state until the creator has reviewed the inventory unless they explicitly asked for an immediate best-effort migration.
When the creator names more than one source ("I used ChatGPT and Claude", "ChatGPT plus my old OpenClaw box"), build one unified inventory, not one per source. Each inventory row gains a Source attribution column alongside the existing fields (source path/origin, what-it-is, Vellum destination, confidence, action, reason).
Dedupe and reconcile across sources:
The unified inventory drives per-source rebind/import routing — each row's action resolves against the source it came from:
chatgpt-import skill (see below; do not parse ZIPs here).references/claude.md.references/chatgpt.md.Keep the existing Review Surface and Port / Review / Re-setup / Disregard flow. Multi-source just means one combined checklist with source labels, not a separate pass per source.
Prefer a rich checklist when an interactive surface is available. The checklist should let the creator mark each item as:
If a rich UI is not available on the current channel, present the same information as a concise markdown table and ask for the creator's choices.
Suggested checklist groups:
Use the most native Vellum primitive available. Prefer existing Vellum setup/import flows over custom conversion. Keep source provenance in notes when useful so the creator can audit where migrated material came from.
For each migrated group, report what changed and what remains pending. If an item is skipped, say why.
Some internals should be rebuilt instead of copied:
When rebuilding, explain the Vellum equivalent and ask whether the creator wants to re-set it up now.
| Source assistant concept | Vellum primitive | Migration guidance |
|---|---|---|
| Name, persona, tone, identity docs, system prompts | Identity, Personality, Avatar, SOUL.md, user persona files | Preserve explicit creator-approved identity/personality material. Convert brittle prompt hacks into plain behavioral guidance. |
| Current focus, scratchpads, working notes | NOW.md, Workspace notes, Memory | Preserve active projects and open loops. Avoid importing stale scratch state as permanent truth. |
| Memory databases, summaries, profiles, user facts | Memory | Extract candidates with the bundled parsers, review with the creator, then follow the Memory Import Guidance flow below. Provenance frontmatter (source:, origin_date:) preserves attribution and original chronology. |
| Conversation history | Conversations and Memory | Import supported structured exports when available. Otherwise summarize useful history into memory candidates rather than dumping logs blindly. |
| Tools, skills, commands, plugins, playbooks | Skills | Recreate as Vellum skills when the capability is still useful. Keep instructions portable; avoid foreign runtime assumptions. |
| MCP servers | MCP | Recreate server registrations and required environment through Vellum's MCP setup flow. Reconnect secrets through the credential vault. |
| Browser automation state, browsing tasks | Browser capability | Recreate workflows and permissions. Do not import cookies or browser profile secrets directly. |
| Computer-use automations | Computer Use capability | Recreate task intent and permission expectations. Verify host-computer access through Vellum's own consent model. |
| Custom dashboards, tools, visual workflows | Apps or Widgets | Persistent interactive tools should become Apps. Transient conversation UI should become Widgets or normal chat flows. |
| Slack, Telegram, email, phone, webhooks | Channels and Integrations | Reconnect channels through Vellum setup skills. Expect some providers, especially Slack, to need fresh setup. |
| Friends, coworkers, allowed users | Contacts and Trusted Contacts | Map relationships into Contacts. Grant channel access through trusted-contact and guardian flows, not direct database edits. |
| Owner/admin identity, approval authority | Guardian Verification | Verify the creator/guardian on each channel needed for secure access and approvals. |
| Secrets, API keys, tokens, OAuth refresh tokens | Credential Vault and OAuth Integrations | Never paste or import raw secrets. Rebind through secure prompts, OAuth connect flows, or provider setup skills. |
| Autonomy settings, allowlists, deny rules | Trust Rules and Permissions | Translate intent, not syntax. Start conservative when semantics are unclear. |
| Timed jobs and reminders | Schedules | Recreate one-shot and recurring tasks using Vellum schedules. Preserve the user-visible intent and delivery channel. |
| Autonomous monitors and polling jobs | Watchers | Rebuild as watchers when the source monitors external events. Reconnect provider credentials first. |
| Periodic self-checks | Heartbeats | Use Vellum heartbeats for agenda-free self-checking, not for specific timed jobs. |
| Pending replies or nudges | Followups | Preserve expected-response workflows as followups when the source tracks sent messages awaiting replies. |
| Reusable action templates and queues | Task Queue | Recreate repeatable work as tasks or queued work items when the creator expects review before completion. |
| Model routing, fast/quality/cost modes, provider keys | Inference Profiles and Provider Connections | Map source behavior to named profiles such as balanced, quality, or cost/speed variants. Reconnect provider credentials safely. |
| Files, projects, notes, attachments | Workspace | Copy useful, non-secret artifacts into the Vellum workspace with clear organization. Leave local worktree artifacts and foreign caches behind. |
Memory import is a review-first pipeline: extract candidates deterministically, review every item with the creator, shape the approved items into v3 article pages, ingest them as a batch, then verify. Nothing is saved unreviewed at any step.
Use the bundled parsers to pull candidates out of the source artifacts. Both emit MemoryImportItem[] JSON ({ text, source, origin_date?, context? }) on stdout and a human-readable inventory on stderr, and both redact credential-shaped values before anything reaches stdout:
ChatGPT non-conversation material (saved memories, custom instructions):
bun run {baseDir}/scripts/parse-chatgpt-memory.ts --file /path/to/chatgpt-export.zipHermes / OpenClaw memory.db snapshots (always a .backup snapshot, never a live DB; see the provider references):
bun run {baseDir}/scripts/parse-agent-memory-db.ts --file /path/to/memory.db.snapshot --source hermes(or --source openclaw)
Claude has no deterministic importer. Fall back to the interview flow: invite the source assistant to produce a portable self-summary and treat its items as the candidate list. Ask for comprehensive but reviewable output: identity and background; preferences and communication style; important relationships; active projects and open loops; durable instructions the creator gave it; meaningful history from recent conversations; uncertainties and low-confidence inferences clearly labeled.
The self-summary is worth collecting for any source assistant that can still answer questions; it complements parser output with material no export captures.
Present the candidate inventory (the parsers' stderr census plus the items themselves) in conversation and let the creator decide what survives. Drop stale, inferred, speculative, or emotionally loaded items unless the creator explicitly keeps them. Never bulk-dump raw parser output into memory: parsers produce candidates, not memories.
Write the approved items as concept pages in a staging directory (for example .mv3/staging/), one .md file per page. Follow the vellum-memory-v3-migration skill's references/v3-wiki-principles.md for the article shape rather than improvising; the essentials are:
summary: field; the lead is the retrieval card).## sections with names that work as navigation..md becomes the slug.links: entries annotated with why-notes: each entry names a target slug plus one line on why the link exists, in the exact format the principles doc shows.source: import:<provider> (e.g. import:chatgpt). Add origin_date: (ISO 8601) when the source material carries a date (a parser-emitted origin_date, or a date the creator confirms); it drives the page's effective recency, so imported pages rank by when their content originally dates from, not by import time. When the original date is unknown, omit the field rather than inventing one; the page then ranks by its write time like any other new page.assistant memory ingest --dir .mv3/staging --dry-runReview the per-page dry-run results (written / skipped / invalid) with the creator, fix any invalid pages, and resolve any warning about a links: or [[wikilink]] target that is neither on disk nor in the staged set (stage the missing page, or make the reference plain prose), then run the same command without --dry-run. Existing slugs are skipped unless --overwrite is passed. If the command fails because the consolidation lock is held, wait for consolidation to finish and retry; do not work around the lock.
assistant memory v3 eval does not apply here: it compares two complete corpora, and an import's staging directory holds only the new pages, not a corpus.)A handful of approved facts does not need the staging pipeline; save them through the normal remember tool instead.
Warning: never bulk-append imported facts to memory/buffer.md. Bulk appends share one minute-stamp and force consolidation to process the whole buffer in a single run; assistant memory ingest exists precisely to bypass that hazard.
When source files are available, inspect them directly and classify them:
For medium- and low-confidence items, ask before importing and prefer converting into reviewed notes or setup tasks.
End with a concise report:
If the migration created follow-up work, offer the next concrete step rather than claiming the migration is complete.
© vellum-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 9 other files (scripts, references) in skills/assistant-migration of vellum-ai/vellum-assistant.
Open the folder on GitHubat commit 844117a
Assistant Migration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Assistant Migration this skillvellum-ai/vellum-assistant | 1.4k | — | ~6.3k | Automated safety check: Pass | MIT | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT | |
| AI SDKvercel-labs/ai-facts | 168 | 20 repos | ~1.2k | Automated safety check: Pass | None | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| PR Design DocOpenHands/OpenHands | 90k | — | ~2.4k | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 |
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
vercel-labs/ai-facts
Answer questions about the AI SDK and help build AI-powered features.
zhayujie/CowAgent
Generates or edits images from text prompts through a Python script that picks an image backend based on which API keys are configured.
OpenHands/OpenHands
For a non-trivial pull request, write a self-contained HTML design doc under the temporary .pr/ directory and link a visibility-appropriate preview in the PR description, so maintainers grasp the…
ReScienceLab/opc-skills
SEO & GEO (Generative Engine Optimization) for websites. An agent skill from ReScienceLab/opc-skills.
alibaba/open-code-review
Runs the ocr command-line tool to review Git changes, a commit or a branch comparison with an AI model, returning line-level comments and optionally applying fixes.
vellum-ai/vellum-assistant
Create and configure a GitHub App so the assistant can push commits, open PRs, and comment under its own bot identity.
vellum-ai/vellum-assistant
Connect a Discord bot to the assistant via the Discord Gateway with guided application creation and intent configuration
vellum-ai/vellum-assistant
Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity
vellum-ai/vellum-assistant
Ingest a large dataset into memory as a skimmed map. An agent skill from vellum-ai/vellum-assistant.
vellum-ai/vellum-assistant
A skill your agent uses when the user wants to build, scaffold, ship, or edit a Vellum plugin that bundles multiple surfaces (hooks, tools, skills, and more) into one installable package.
vellum-ai/vellum-assistant
Connect a Slack app to the Vellum Assistant via Socket Mode.
Works with
Migrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved…. Assistant Migration is an agent skill from vellum-ai/vellum-assistant. Migrate from ChatGPT, Claude, OpenClaw, Hermes, Manus, and other AI assistants into Vellum by inspecting their data exports, conversation archives, files, prompts, custom instructions, memory, saved memories, tools, GPTs, workflows, integrations, and relationships, then mapping as much as safely possible into Vellum primitives.
Run `npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a claude-code`. Or copy the skill folder (skills/assistant-migration in vellum-ai/vellum-assistant) into .claude/skills/assistant-migration in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a codex`. Or copy the skill folder (skills/assistant-migration in vellum-ai/vellum-assistant) into .agents/skills/assistant-migration in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vellum-ai/vellum-assistant --skill assistant-migration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/assistant-migration, .gemini/skills/assistant-migration, .github/skills/assistant-migration and .opencode/skills/assistant-migration in your project.
Going by SKILL.md and its folder, Assistant Migration needs TypeScript for the scripts in its folder and the command-line tools its instructions call (bun). Our summary lists: Node.js. Compatibility (from SKILL.md): Designed for Vellum personal assistants.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Assistant Migration is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 6.3k tokens (SKILL.md is roughly 25k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.9k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Assistant Migration: Geo Fundamentals (wasp-lang/wasp, 19k stars), AI SDK (vercel-labs/ai-facts, 168 stars), AI Image Generation and Editing (zhayujie/CowAgent, 47k stars) and PR Design Doc (OpenHands/OpenHands, 90k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vellum-ai (a GitHub organization) maintains it in vellum-ai/vellum-assistant, which has 1,400 GitHub stars. The repository holds 108 skills in this directory. The repository was last updated on October 9, 2026.
Source: vellum-ai/vellum-assistant on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.