Produit & Go-to-marketSûr100100/100

Reward Recommendations (Microsoft)

Gives a Marketing Leader preference-matched reward options without creating offers or issuing benefits.

ou envoie-le directement à ton agent.

Installer dans ton projet

$ curl -fsSL https://arboristhree.xyz/cli/install-skill.mjs -o /tmp/arboris-install-skill.mjs && node /tmp/arboris-install-skill.mjs reward-recommendations__microsoft-aibast-agents-library__solutions-customer-loyalty-rewards-manual-skills-4d869a32c879

Microsoft

microsoft/aibast-agents-library

Ouvrir le dépôt GitHub

Contenu à copier

---
name: review-only-reward-options
description: Gives a Marketing Leader preference-matched reward options without creating offers or issuing benefits.
metadata:
  origin: Microsoft
---
# Review-only reward options

Match broad stated synthetic preferences to catalog concepts within the
synthetic balance. Present options and policy questions. Do not contact anyone,
create an offer, issue a reward, redeem points, refund, order, or purchase.

Colle ce Markdown dans ton agent ou utilise les boutons ci-dessus pour l’écrire dans ton projet.

Ce que fait Reward Recommendations (Microsoft)

Applique les pratiques du skill reward-recommendations__microsoft-aibast-agents-library__solutions-customer-loyalty-rewards-manual-skills-4d869a32c879.

Comment utiliser Reward Recommendations (Microsoft)

Copie le prompt

Un clic copie le prompt packagé (ou l'envoie à ton agent).

L'agent installe le skill

Il ajoute le SKILL.md et ses ressources à ton projet.

Activation automatique

Le skill s'active dès que le contexte correspond.

Déclencheurs pour Reward Recommendations (Microsoft)

Dis simplement à ton agent quelque chose comme :

Applique le skill reward-recommendations__microsoft-aibast-agents-library__solutions-customer-loyalty-rewards-manual-skills-4d869a32c879 à cette tâche

Utilise reward-recommendations__microsoft-aibast-agents-library__solutions-customer-loyalty-rewards-manual-skills-4d869a32c879 pour améliorer cette implémentation

Passe en revue ce sujet avec reward-recommendations__microsoft-aibast-agents-library__solutions-customer-loyalty-rewards-manual-skills-4d869a32c879

Skills liés à Reward Recommendations (Microsoft)

Abandonment Analysis (Microsoft)

Helps a Marketing Manager review anonymous synthetic abandonment patterns without contacting shoppers.

Add Seo (Microsoft)

Adds SEO essentials to a Power Pages code site, including robots.txt, sitemap.xml, meta tags, Open Graph tags, and favicon configuration. Use when the user wants to improve search engine optimization or make their site more searchable.

ai-seo

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.