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Draft prioritized cross-sell recommendations and a reviewable engagement plan from synthetic data.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "cross-selling-recommendation-engine" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/aibast-agents-library/main/solutions/cross-selling/manual/skills/recommendation-engine/SKILL.md 2. Save it as ~/.claude/skills/recommendation-engine/SKILL.md 3. Reload skills and tell me it's ready
Using the recommendation_engine operation, draft prioritized product recommendations and a reviewable engagement plan for synthetic customer CUST-001. Use only the fixed synthetic snapshot and do not send outreach.
Returns prioritized product recommendations, a reviewable engagement plan, and an explicit evidence boundary.
Based on the two uploaded knowledge files, use exact synthetic identifiers to generate read-only decision support with Prioritized Recommendations, Draft Engagement Plan, and Evidence boundary.
Produces recommendations strictly grounded in synthetic test evidence, without claiming outreach, CRM updates, or task creation.
Create a cross-selling opportunity draft for CUST-001, marking all recommendations, value judgments, and next steps as requiring human review, and do not use external data.
Generates a draft that authorized humans can review, clearly framed as read-only decision support.
Sales enablement or marketing teams can draft cross-sell product recommendations for a specific customer from a fixed synthetic snapshot. The result is for human review and not for direct customer outreach.
Teams can demonstrate how prioritized recommendations and an engagement plan are generated from synthetic records in a demo or test setting. The workflow explicitly forbids CRM changes, task creation, or outbound communication.
Analysts can use this skill to organize recommendation evidence while preserving the fixed evidence boundary. This helps reviewers verify synthetic names, dates, amounts, and scores before human approval.
The README describes a cross-selling recommendation engine that drafts prioritized product recommendations and a reviewable engagement plan for synthetic customer CUST-001. It must use only the synthetic data source and the two uploaded knowledge files, without browsing or external enrichment. The output is strictly read-only decision support and must include Prioritized Recommendations, Draft Engagement Plan, and an explicit Evidence boundary.
Enablement Manager
recommendation_enginesynthetic onlyrecommendation_engine.Prioritized Recommendations, Draft Engagement Plan, Evidence boundary anchors.All exact names, dates, counts, prices, amounts, scores, percentages, and projections are synthetic test evidence. The response is read-only decision support. Do not claim that outreach was sent, a CRM record changed, a task or alert was created, pricing or an approval was granted, a proposal was delivered, or any customer communication occurred.
Draft prioritized product recommendations and a reviewable engagement plan for synthetic customer CUST-001 without sending outreach.
The response must include Prioritized Recommendations, Draft Engagement Plan, Evidence boundary and preserve the explicit synthetic evidence boundary.
It drafts prioritized product recommendations and a reviewable engagement plan for synthetic customer CUST-001. The output is read-only decision support and does not send outreach or execute business actions.
The documentation says it can use only the synthetic data source and only the two uploaded knowledge files in the package. It must not browse, enrich, infer, or use external data.
No. The documentation explicitly forbids outreach, CRM updates, task or alert creation, meeting scheduling, and other customer-facing or system-changing actions.
Rank a fictional contract portfolio to prioritize legal review attention.
Explain synthetic cross-sell affinity rules and benchmark assumptions from fixed evidence.
Compare contract clauses against internal policy requirements and identify gaps.
Draft prioritized amendment positions and legal escalation points for contract renegotiations.
Scan synthetic customer records to find evidence-backed cross-sell product gaps.
Compare synthetic cross-sell portfolio value scenarios for human-reviewed decision support.
Prioritize churn reviews with transparent evidence and suggested next steps.
Prepare reviewable retention and service-recovery options for churn-related customer cases.
Research prospects and draft personalized outreach emails with stronger relevance and response potential.
Generate polished sales assets from deal context for customer-ready sharing.
Build weighted sales forecasts with scenario planning, commit splits, and gap analysis.
Qualify leads, score ICP fit, forecast pipeline, and plan outreach.