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Analyze loyalty tier thresholds, perks, progress, and tradeoffs without changing status.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "loyalty-tier-structure-analysis" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/aibast-agents-library/main/solutions/customer-loyalty-rewards/manual/skills/tier-analysis/SKILL.md 2. Save it as ~/.claude/skills/tier-analysis/SKILL.md 3. Reload skills and tell me it's ready
Using a fixed tier model, compare the pros and cons of the current loyalty program tier thresholds. Explain how they affect perceived member progress and structural balance, but do not change any member status.
An analysis of tier threshold differences, progress impact, and structural tradeoffs, with no actual status changes.
Analyze whether the points multipliers and perk combinations across loyalty tiers are well structured. Identify which designs may improve appeal and which may make tiers insufficiently differentiated. Analysis only; do not issue perks or adjust points.
An evaluation of multipliers, perks, and tier differentiation, clearly limited to analysis.
Review synthetic member progress under the current fixed tier model. Analyze whether advancement paths between tiers are clear and whether there are structural imbalances; do not contact members or create any purchase records.
A report on progress clarity and tier structure issues, without any operational actions.
A loyalty program lead can use it to compare thresholds, multipliers, and perks when reviewing an existing tier system. It is for evaluating structural tradeoffs, not directly changing member eligibility.
When a team needs to discuss whether a tier design makes sense, this skill helps analyze progress and tier structure. It explicitly separates analysis from eligibility handling and does not modify tiers, points, or perks.
The README describes a skill for analyzing loyalty tier structures using a fixed tier model. It focuses on comparing thresholds, multipliers, perks, progress, and broader structural tradeoffs. The document strongly distinguishes analysis from eligibility operations: the skill should not change a member’s tier, issue perks, alter points, contact members, or create purchases.
Compare threshold, multiplier, perks, progress, and structural tradeoffs using the fixed tier model. Distinguish analysis from eligibility. Do not change a tier, issue a perk, alter points, contact a member, or create a purchase.
It analyzes loyalty program tier thresholds, multipliers, perks, progress, and structural tradeoffs. Based on the description, it is analysis-only and does not change member status.
No. The documentation explicitly says not to change a tier, issue a perk, alter points, contact a member, or create a purchase.
The documentation says it uses a fixed tier model to compare thresholds, multipliers, perks, progress, and structural tradeoffs. For more details, see the source repository.
Generates controlled implementation checklists for human review.
Creates a deterministic reconsideration evidence packet from synthetic source files.
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Find each line’s bottleneck and recommend which station to address first.
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Prepare reviewable retention and service-recovery options for churn-related customer cases.
Get a synthetic health overview of a loyalty program without changing it.
Review product metrics, spot trends, and get actionable improvement recommendations.
Generate a synthetic points summary explanation without changing the ledger.
Prioritize churn reviews with transparent evidence and suggested next steps.
Answer metric questions, analyze trends, compare segments, and draft data reports.
Analyze compensation bands, offer competitiveness, equity grants, and retention risks.