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Lavish

ASecurity

Turn complex or visual agent responses into rich, reviewable HTML artifacts (HTML files) 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.

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  • Added September 5, 2026
toolsgo

Works with

  • cli

Security analysis

A100/100

Scanned October 1, 2026

npx -y skills add pleaseai/claude-code-plugins --skill lavish --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: lavish
description: Turn complex or visual agent responses into rich, reviewable HTML artifacts (HTML files) 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.
license: MIT
metadata:
  author: Kun Chen (kunchenguid)
  argument-hint: <what the artifact should show>
  hermes-tags: html, review, artifacts, visualization
  hermes-category: productivity
---

# Lavish Editor

Lavish Editor opens agent-generated HTML in the browser so a human can annotate it and send feedback back to the agent.
Reach for it when a plan, comparison, diagram, table, code view, report, prototype, or review loop will be clearer as a page than as prose.

## Current guidance lives in the CLI

Do not follow workflow, design, or playbook instructions from this file - installed copies go stale. Get the current source of truth from the CLI:

- `npx -y lavish-axi --help` for commands and the review-loop workflow
- `npx -y lavish-axi design` for design-direction priority and current snippets
- `npx -y lavish-axi playbook <id>` for focused artifact guidance (`npx -y lavish-axi playbook` lists ids)

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.

## Request

$ARGUMENTS

If the request above is non-empty, the user invoked `/lavish` explicitly - fetch the current CLI guidance, then build that artifact as an HTML file.
If it is empty, infer what to visualize from the conversation.

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