LobeHub Interactive Prototype
lobehub/lobehub
Builds single-file interactive HTML prototypes rendered with the real LobeHub UI components and written as production-style React, so they can later be split into files.
Turn complex or visual agent responses into rich, reviewable HTML artifacts the user can annotate and send feedback on, using the lavish-axi CLI.
The automated check flagged lines worth reading first. See the safety section below.
$ npx skills add layer5io/sistent --skill lavish -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install layer5io/sistent lavish --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/layer5io/sistent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/lavish .claude/skills/lavish && 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 "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .claude/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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/layer5io/sistent/tree/master/.agents/skills/lavishType 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 layer5io/sistent --skill lavish -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install layer5io/sistent lavish --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/layer5io/sistent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/lavish .agents/skills/lavish && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .agents/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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 layer5io/sistent --skill lavish -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install layer5io/sistent lavish --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/layer5io/sistent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/lavish .cursor/skills/lavish && 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 "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .cursor/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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/layer5io/sistent.git --path .agents/skills/lavish--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 layer5io/sistent --skill lavish -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install layer5io/sistent lavish --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/layer5io/sistent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/lavish .gemini/skills/lavish && 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 "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .gemini/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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 layer5io/sistent lavishInstalls 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 layer5io/sistent --skill lavish -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/layer5io/sistent.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/lavish .github/skills/lavish && 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 "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .github/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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 layer5io/sistent --skill lavish -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install layer5io/sistent lavish --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/layer5io/sistent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/lavish .opencode/skills/lavish && 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 "lavish" agent skill from https://github.com/layer5io/sistent/tree/master/.agents/skills/lavish into .opencode/skills/lavish/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lavish", 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.
lavishTurn complex or visual agent responses into rich, reviewable HTML artifacts the user can annotate and send feedback on, using the lavish-axi CLI.
Lavish is an agent skill from layer5io/sistent. Turn complex or visual agent responses into rich, reviewable HTML artifacts the user can annotate and send feedback on, using the lavish-axi CLI. Use when about to give a plan, comparison, diagram, table, code diff, report, or anything easier to grasp visually than as prose.
Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Frontend & Design, covering HTML artifacts. The licence is Apache-2.0.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 672bc14. 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.
Shell commands in SKILL.md call:
npxnodenpmFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
ht-ml.appFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
LAVISH_AXI_HTML_APP_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Lavish loads about 3.2k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 1,860 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 patterns that need a careful read before installing.
Do not tell the user the artifact is being monitored until that wake path is live.llback into the surrounding supervisor. Do not tell the user the artifact is being monitored until that wake path is livAutomated 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); files beside SKILL.md are not scanned.
The full file from layer5io/sistent at commit 672bc14, republished under its Apache-2.0 licence (© layer5io). 1,860 words, ~3,195 tokens.
.claude/skills/lavish/SKILL.md (or your agent's skills folder).Lavish Editor helps agents turn rich HTML artifacts into collaborative human review surfaces. Whenever you are about to give user a complex response that will be easier to understand via a rich / interactive page, consider using Lavish Editor. First generate an interactive HTML artifact according to user request, then run npx -y lavish-axi <html-file> so the user can visually review it, annotate elements or selected text, queue prompts, and send feedback back through npx -y lavish-axi poll.
You do not need lavish-axi installed globally - invoke it with npx -y lavish-axi <html-file>.
If lavish-axi output shows a follow-up command starting with lavish-axi, run it as npx -y lavish-axi ... instead.
In restricted subprocess sandboxes, CI, or agent harnesses where npx -y exits opaquely (for example with status 216), use an already-installed copy directly: node "$(npm root)/lavish-axi/dist/cli.mjs" <html-file> for a local install, node "$(npm root -g)/lavish-axi/dist/cli.mjs" <html-file> for a global install, or the bare lavish-axi <html-file> bin after installing once.
$ARGUMENTS
If the request above is non-empty, the user invoked /lavish explicitly - build an HTML artifact for that request now, following the workflow below.
If it is empty, infer what to visualize from the conversation.
Use lavish-axi when the user asks for a visual artifact, HTML explainer, interactive prototype, review surface, product or technical plan, comparison, report, or browser-based feedback loop
.lavish/<name>.html in the working directory).npx -y lavish-axi <html-file> to open or resume a review session in the browser.npx -y lavish-axi poll <html-file> to long-poll for the user's annotations, queued prompts, and browser-proven severe layout failures returned as layout_warnings.
On the first poll, prefer --agent-reply "<one-line summary of what you built and what to review first>" so the conversation panel opens with context.
The poll stays silent until the user acts or the real browser proves meaningful content is inaccessible or unusable - leave it running, never kill it.
Cosmetic, intentional, transient, tiny, and uncertain observations remain silent.
Keep the poll in the foreground by default and let it return the feedback directly to the agent.
A background poll is allowed only through a harness-native tracked background-job facility whose completion result is guaranteed to resume or notify the same agent.
Never use nohup, shell &, disown, redirected fire-and-forget processes, or a detached terminal without an explicit verified callback merely to keep polling alive.
If the harness has no completion-aware background facility, use the foreground poll or first wire a verified wake callback into the surrounding supervisor.
Do not tell the user the artifact is being monitored until that wake path is live.
If the poll gets killed or times out anyway, just re-run it - queued feedback is never lost.layout_warnings, follow the returned next_step: repair the severe failure and re-check it before involving the human.--agent-reply "<message>" to reply in the browser and keep the loop going under the same foreground-or-verified-wake-path rule.npx -y lavish-axi end <html-file> when the review is finished.Send & End ends the session. Its final feedback is still delivered once. After that response, polling stops, and the agent must not reopen the session uninvited. Deliver any remaining updates directly in this conversation.Run npx -y lavish-axi playbook <id> for focused, detailed guidance on any of these.
One artifact often combines several playbooks (for example a plan that includes a comparison and a diagram), so MUST open each matching playbook before writing HTML.
For flows, architecture, state, or sequence diagrams, do not hand-build boxes-and-arrows from div/flexbox; open the diagram playbook and use the theme-aware Mermaid snippet from npx -y lavish-axi design unless SVG is needed for richly annotated nodes.
diagram - Map relationships, flows, state, and architecturetable - Turn dense records into scan-friendly review surfacescomparison - Show options, tradeoffs, and current vs target behaviorplan - Explain a product or technical plan before implementationcode - Render source code, code files, patches, PR diffs, and before/after code inside Lavish artifactsinput - Must be used when the agent needs to collect user input on decisions, choices, preferences, triage, scope, or other structured feedback from within the artifactslides - Create a deliberate presentation when slides are requestednpx -y lavish-axi <html-file> to open or resume a Lavish Editor session. If the user explicitly ended the session from the browser, this refuses to reopen it and explains why instead of reopening uninvited - pass --reopen only when the user asks for further review or something important needs their visual attention.lavish// to those asset paths - root paths won't worknpx -y lavish-axi poll <html-file> to wait for user feedback or browser-proven severe layout failures. It long-polls and stays silent until the user sends feedback, ends the session, or the real browser proves meaningful content is inaccessible or unusable, so leave it running - never kill it. Repair and re-check every returned layout failure before involving the human; cosmetic, intentional, transient, tiny, and uncertain observations stay silent. Keep the poll in the foreground by default and let it return the feedback directly to the agent. A background poll is allowed only through a harness-native tracked background-job facility whose completion result is guaranteed to resume or notify the same agent. Never use nohup, shell &, disown, redirected fire-and-forget processes, or a detached terminal without an explicit verified callback merely to keep polling alive. If the harness has no completion-aware background facility, use the foreground poll or first wire a verified wake callback into the surrounding supervisor. Do not tell the user the artifact is being monitored until that wake path is live. If the poll gets killed or times out anyway, just re-run it - queued feedback is never lost. Send & End ends the session. Its final feedback is still delivered once. After that response, polling stops, and the agent must not reopen the session uninvited..mermaid containers become embedded, editable Excalidraw whiteboards in the browser (click a diagram to unlock editing; a Fullscreen action opens it over the whole viewport) - flowchart, sequence, class, ER, and state diagrams convert to editable shapes; other types embed as an image to draw on. Scenes autosave locally; when a reload detects a changed Mermaid source, the reviewer explicitly chooses to re-convert and discard saved edits or keep editing the saved scene. Standalone and exported copies still render plain Mermaid. Queue feedback adds a prompt to the Conversation panel; when the user sends it, poll returns a tag "whiteboard" prompt carrying a bounded edit summary plus local scenePath (.excalidraw JSON) and previewPath (PNG) files - read the summary first, open the files only when needed, then apply the edits by updating the Mermaid source in the artifact (never try to write the scene back)npx -y lavish-axi end <html-file> to end a session as the agent - ending it this way still allows a plain reopen later. When the user ends it from the browser instead, a later npx -y lavish-axi <html-file> refuses to reopen it without --reopennpx -y lavish-axi export <html-file> [--out <path>] to write a portable copy of the artifact - one HTML file with its LOCAL assets inlined - so it opens with no Lavish server and no sibling files. Remote CDN/font references are left as links, so it needs network to render those. Users can also export from the browser chrome's overflow menunpx -y lavish-axi share <html-file> [--password <pw>] [--token <t>] to publish the artifact on ht-ml.app (https://ht-ml.app), a third-party hosting service not part of Lavish, and get back a visitable URL. Shares are PUBLIC by default, so anyone with the link can open them. Pass --password to publish a PRIVATE password-protected page; viewers must supply the password to view. Local assets are inlined; remote refs load over the network. It returns the url plus a secret update_key for managing the page later. Use --token or LAVISH_AXI_HTML_APP_TOKEN only when you have an optional bearer token; it is never required. Users can also publish from the browser chrome's overflow menunpx -y lavish-axi stop to shut down the background server (it also self-stops when idle or after the last session ends with nothing connected)npx -y lavish-axi playbook <playbook_id> for focused artifact guidance. One artifact often combines several playbooks (for example a plan that includes a comparison and a diagram), so MUST open each matching playbook before writing HTML.npx -y lavish-axi design for a content-to-playbook router, a copy-pasteable CDN snippet, a Mermaid CDN snippet/init for diagrams, and the DaisyUI component reference. When you deliver the artifact, state which of the three design sources you used and why.© layer5io, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/lavish of layer5io/sistent.
Open the folder on GitHubat commit 672bc14
We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in layer5io/sistent, which our catalogue first saw on October 7, 2026.
Lavish 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 |
|---|---|---|---|---|---|---|
| Lavish this skilllayer5io/sistent | 138 | 3 repos | ~3.2k | Automated safety check: Warn | Apache-2.0 | |
| LobeHub Interactive Prototypelobehub/lobehub | 83k | — | ~1.6k | Automated safety check: Pass | Custom licence | |
| Paperclip Pagepaperclipai/paperclip | 98k | — | ~1k | Automated safety check: Pass | MIT | |
| Openkb Deck NeonVectifyAI/OpenKB | 4.7k | 1 repos | ~4.3k | Automated safety check: Pass | Apache-2.0 | |
| Webhome Homepage Builderwebhtv/webhtv | 1.7k | — | ~3.8k | Automated safety check: Pass | GPL-3.0 | |
| Solo Artifactssolo-agent/solo | 697 | — | ~961 | Automated safety check: Pass | MIT |
lobehub/lobehub
Builds single-file interactive HTML prototypes rendered with the real LobeHub UI components and written as production-style React, so they can later be split into files.
paperclipai/paperclip
Publish static HTML pages and asset folders to the Paperclip S3/CloudFront page host.
VectifyAI/OpenKB
A skill your agent uses when the user asks the openkb chat to make a deck / slide presentation / PPT / slides / 演示稿 / 幻灯片 from their compiled KB content AND wants a dark, high-tech, neon / glow /…
webhtv/webhtv
Build, review, debug, reverse-engineer data sources for, and package FongMi/WebHome custom homepage single-file HTML.
solo-agent/solo
A skill your agent uses when a Solo task or thread should become an interactive, reviewable, self-contained HTML artifact for progress/status, review/decision, or comparison/leaderboard work inside…
QuZhan51496/paper2anything
Convert an academic paper PDF into a publish-ready, self-contained single-page project homepage (a self-contained index.html) — the kind of paper landing page researchers host on GitHub Pages.
layer5io/sistent
Control a Chrome browser session through the chrome-devtools-axi CLI - navigate, snapshot, click, fill forms, run JavaScript, inspect console and network, take screenshots, audit performance.
layer5io/sistent
Runbook for cutting a release of @sistent/sistent to npm. An agent skill from layer5io/sistent.
layer5io/sistent
Operate GitHub through the gh-axi CLI - issues, pull requests, workflow runs, workflows, releases, repositories, labels, Projects (v2), Actions secrets and variables, search, and raw API access.
layer5io/sistent
Report local Claude, Codex, Cursor, GitHub Copilot, and Grok quota windows via the quota-axi CLI - remaining percentages, reset times, and provider status read from local auth sources, with no…
layer5io/sistent
Iterate on a PR until CI passes. An agent skill from layer5io/sistent.
Categories
Turn complex or visual agent responses into rich, reviewable HTML artifacts the user can annotate and send feedback on, using the lavish-axi CLI. Lavish is an agent skill from layer5io/sistent. Turn complex or visual agent responses into rich, reviewable HTML artifacts the user can annotate and send feedback on, using the lavish-axi CLI.
Lavish fits situations like: about to give a plan; anything easier to grasp visually than as prose.
Run `npx skills add layer5io/sistent --skill lavish -a claude-code`. Or copy the skill folder (.agents/skills/lavish in layer5io/sistent) into .claude/skills/lavish in your project. Claude Code loads it when a task matches its description.
Run `npx skills add layer5io/sistent --skill lavish -a codex`. Or copy the skill folder (.agents/skills/lavish in layer5io/sistent) into .agents/skills/lavish 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 layer5io/sistent --skill lavish -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lavish, .gemini/skills/lavish, .github/skills/lavish and .opencode/skills/lavish in your project.
Going by SKILL.md and its folder, Lavish needs the command-line tools its instructions call (npx, node and npm) and credentials named LAVISH_AXI_HTML_APP_TOKEN. Our summary lists: Node.js; A credential in LAVISH_AXI_HTML_APP_TOKEN.
SKILL.md names 1 domain. As links in the text: ht-ml.app. This is read from the text; nothing was executed.
Our automated static check of SKILL.md flagged 2 warning(s): contains instruction-override wording (e.g. “without asking the user”). Read the flagged lines before installing; the check is not a guarantee either way.
Lavish is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Lavish: LobeHub Interactive Prototype (lobehub/lobehub, 83k stars), Paperclip Page (paperclipai/paperclip, 98k stars), Openkb Deck Neon (VectifyAI/OpenKB, 4.7k stars) and Webhome Homepage Builder (webhtv/webhtv, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
layer5io (a GitHub organization) maintains it in layer5io/sistent, which has 138 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on October 2, 2026.
Source: layer5io/sistent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.