Your AI artifacts have a home now. Index, search, preview, share with one click, and use your past work as the style guide for your next one.
"I've started preferring HTML as an output format instead of Markdown. The added expressiveness means I get overall better output, and the chance of someone actually reading your spec, report or PR writeup is much higher if it's in HTML. … When writing this article, I asked Claude Code to read through my code folder and find all the HTML files I've generated, group and categorize them …"— Thariq,
(Claude Code team)[The Unreasonable Effectiveness of HTML]
Artifold is that library. If you're shifting from Markdown to HTML for specs, reports, designs, prototypes, throwaway editors — the way Thariq describes — Artifold is where they live.
You've been making a lot of HTML with AI lately: Claude Artifacts,
ChatGPT Canvas, v0, Lovable, Cursor. They land in ~/Downloads
or some project folder, you bookmark a tab, you mean to come back to that ROI calculator you made three weeks ago — and you can't find it.
That's the whole reason this exists. I made a 30-day workout tracker for my partner, lost it in a maze of folders, regenerated a worse version, and decided to just build the index myself.
Local-first, fast, runs entirely on your machine. Plus the part where, when you do want to share an artifact, it's one click to a permanent public URL.
Click any card → hit the share icon → in ~30 seconds you get back a
permanent URL like https://you.github.io/artifold-share/abc12345.html
that you can paste into iMessage, Slack, email, anywhere. URL is copied to your clipboard automatically.
Free forever (uses your GitHub Pages quota — no Artifold infrastructure, no sign-up, no per-share fees, no expiry). Anyone with the link sees the fully-rendered report; recipient needs nothing installed.
Sidebar filters by tool, status (shared / local), category, date. ⌘K palette to jump to anything by name, prompt, or intent. Click → in-app preview pane, no tab spam. Dark/light themes. Live auto-rescan — drop a new file in any watched folder and it appears within seconds.
→ See the side-by-side gallery: four prompts run through
claude-sonnet-4
twice— once plainly, once via
/craft
. Same model, same prompt, visibly different output.After installing the Claude Code skill, type /craft a 30-day strength tracker for a beginner
in any session. The skill:
- Reads your library to see styles you've used, then deliberately picks
a
differentdirection so your next artifact doesn't look like the last one (the "all AI output looks the same" problem, actively fought) - OR inherits a specific style:
/craft a poker probability explainer, like dobble
— pulls dobble's actual CSS as the design baseline - Applies 12 opinionated design principles distilled from Refactoring UI, Linear, and Vercel/Geist (every one cited)
- Avoids 15 specific AI-slop signatures (purple-gradient hero, identical bento cards, decorative emoji on every list item, glassmorphism, etc.)
- Saves to
~/artifold-inbox/2026-05-26-<topic>.html
— auto-indexed in Artifold within ~2 seconds
Your past work becomes your style guide for the next one. The loop closes.
If you have Claude Code, paste this prompt — Claude figures out the rest, installs everything, and walks you through first-run:
Tip
Copy this into Claude Code:
Install Artifold from https://github.com/shubhamgoel27/artifold using pipx
(or pip if pipx isn't installed). Then run `artifold init` and help me
pick a folder to watch. After that, run `artifold install-skill` to set
up the /craft skill. Open the dashboard when ready and tell me what
to try first.
That's the whole install. No terminal commands to memorize, no dependencies to debug — Claude handles the awkward parts.
If you'd rather drive:
pipx install artifold # or: pip install artifold
artifold init # interactive wizard
artifold # serves dashboard + opens browser
artifold install-skill # adds /craft to ~/.claude/skills/
Don't have pipx
? Run brew install pipx
(mac) or python -m pip install --user pipx
(anywhere), then the above.
/craft a one-pager comparing three SF apartments
/craft a 30-day strength tracker, like my last one
/craft a probability explainer for poker, in the style of dobble
(Restart Claude Code once after artifold install-skill
so the skill loads.)
The first run installs Playwright's headless Chromium (~170 MB) for artifact thumbnails. After that, only new/changed files re-shoot.
Auto-indexes every *.html
in your watched folders. Groups
-v2
, (1)
, print
variants into one card with a version dropdown.
Skips templates, .git
repos, and anything buried 3 levels deep — your library stays clean even when your folders aren't.
Source-aware — fingerprints Claude / ChatGPT / v0 / Lovable / Bolt
/ Gemini artifacts from HTML markers, tags each card with the tool that
made it. Also reads <meta name="artifold:*">
tags (which the /craft
skill emits) for zero-effort provenance.
Visual — every artifact gets a real screenshot thumbnail. Click a card → slide-out preview pane with tabs for Provenance (source URL, prompt, model, tags) and Design (palette swatches, fonts, mood flags).
Live — artifold serve
watches your folders. Drop in a new artifact and it appears in the dashboard within ~2 seconds, no refresh.
Searchable — ⌘K palette runs across titles, prompts, intents, and exposed actions (toggle theme, switch view, rescan, import). Linear / Raycast pattern.
artifold # default: scan + serve + open browser
artifold init # interactive setup wizard
artifold add <dir> # watch another folder
artifold roots # list watched folders
artifold scan # one-shot rescan
artifold open # open the existing dashboard
artifold share <file> # publish to public URL + copy to clipboard
artifold share --list # all shares
artifold share --revoke <id> # take a public share down
artifold import <url> # fetch a public Claude/v0/Lovable share URL
artifold link <file> --tool claude --source URL --prompt "..."
artifold info <file> # show provenance for a file
artifold designs # list design fingerprints
artifold designs <id> --template # dump CSS + skeleton (paste into Claude)
artifold inbox [topic] # print the canonical path for a new artifact
artifold install-skill # install /craft into ~/.claude/skills/
artifold doctor # check setup; tells you exactly what to fix
~/Library/Application Support/artifold/config.json
on macOS,
~/.config/artifold/config.json
on Linux:
{
"roots": ["/Users/me/Downloads", "/Users/me/work"],
"allow_repos": [], // dirs with their own .git to include anyway
"max_depth": 3,
"drop_dir": null, // where `artifold import` saves (default ~/artifold-inbox)
"enable_intent": false, // opt-in LLM intent metadata (Claude Haiku)
"categories": { // extend the auto-tag keywords
"Research": ["paper", "experiment", "ablation"]
}
}
Cache (thumbnails, manifest, dashboard, Playwright Chromium) lives
under ~/Library/Caches/artifold/
. Wiping it just regenerates everything from your real files — cache is replaceable, your source files are sacred.
| Key | What |
|---|---|
⌘K / Ctrl+K |
|
| palette (actions + artifact search) | |
↵ |
|
| open selected in preview / run action | |
⇧↵ |
|
| open selected in new tab | |
Esc |
|
| close palette / preview | |
/ |
|
| focus the search box | |
| Click card | open in preview pane (in-app, no tab spam) |
⌘ /Ctrl -click |
|
| open in a new browser tab |
Artifold's core is fully local — no LLM, no network, no API key required.
If you want richer metadata (a one-line intent per artifact, topic tags, audience detection — used for smarter search):
pipx install 'artifold[intent]'
export ANTHROPIC_API_KEY=sk-ant-...
artifold scan --intent
~$0.003 per artifact with Claude Haiku, cached forever by content hash
so re-scans are free. ~$0.05 for 15 artifacts. Toggle off with
artifold scan --no-intent
. Skip the extra and the feature simply doesn't appear.
Not a cloud product. Nothing leaves your machine unless you explicitlyartifold share
. There's no sign-up, no account, no Artifold server somewhere. Your library is~/artifold-inbox/
and the dirs you pointed it at — that's it.Not a replacement for git or your existing organization. It's alenson whatever you already have.Not opinionated about where your files live. Multi-root by design. Want it to watch~/Downloads
+~/Documents
+~/work/reports
? Runartifold add
three times.Not trying to be everything for everyone. Built for the specific pain of "where did I put that thing I generated last month."
A artifold is a working collection of pages that informs your next piece of work. Your past artifacts become the reference set for the next one. It's not an archive (cold storage), it's a working library.
The PyPI package is artifold
because artifold
was taken. CLI command is
artifold
. Same pattern as open-interpreter
/ interpreter
.
v0.5.2, alpha — live on PyPI. Tested on macOS Sequoia; Linux should work; Windows untested. Single-developer project made in evenings — issues + PRs welcome, but I'm shipping what I personally use rather than what's broadly polished. The /craft gallery shows side-by-side outputs (default Claude vs
/craft
) on four prompts through Opus 4.7 — if you want to see what the skill actually does before installing, start there.If you try it and something feels off, open an issue — even one line is helpful, "the X button is confusing" is exactly the feedback that improves things.
In rough priority order:
Mobile dashboard— currently breaks below 760px -
— opt-in consolidation intoartifold adopt <file>
~/artifold-inbox/
for existing files (keeping multi-root for those who want it) -
Cloudflare Pages backend forartifold share
(alternative to GH Pages for users withoutgh
CLI) -
— direct one-command generation, opt-in viaartifold generate --like <id>
[intent]
extra -
Markdown rendering— first-class support for*.md
Semantic search— when you remember the gist but not the title - Version diff view— when you iterate v1/v2/v3, see what changed - A real test suite— currently human-tested
@shubhamgoel27 — built because I genuinely needed it. If you find it useful, starring the repo is the single best thing you can do so other people building with AI find it.
The /craft
skill took real research to make non-generic — the 12 design principles trace to Refactoring UI chapters, Linear's Method, Vercel's Geist, and a couple of recent AI-slop critique articles. If you ship cool reports with it, tag me — I love seeing what people make.
MIT