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.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/kunchenguid/lavish-axi --skill lavish

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

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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