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.
Scanned 9/5/2026
Install to Claude Code
npx -y skills add pleaseai/claude-code-plugins --skill lavish --agent claude-codeInstalls into .claude/skills of the current project.
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---
description: "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."
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.
If it is empty, infer what to visualize from the conversation.
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