kunchenguid/lavish-axi

lavish

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.

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/kunchenguid/lavish-axi --skill lavish

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

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 reply --help to post an agent reply and exit once the server accepts it, when you are not about to long-poll
  • 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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