loyalty-modeling

I noticed you're tackling the complexity of predictive loyalty modeling—that's a meaty problem where small implementation details can make the difference between useful insights and noise. Your score of 64 suggests the foundation is solid, but there might be some gaps in how the skill guides developers through the trickier parts of the system.

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 64/100, solidly in D territory. This is based on Anthropic's skill grading standards across five pillars. Your strongest area is Spec Compliance (11/15)—the YAML and naming conventions are locked down. The weakest is Utility (11/20)—the framework exists but lacks the concrete templates, examples, and validation steps that would make it actually actionable for someone building a loyalty model.

What's Working Well

• Valid YAML structure with required frontmatter fields in place
• Hyphen-case naming follows conventions properly
• Clear component breakdown (Inputs, Calculations, Outputs, Validation) provides decent conceptual scaffolding
• Modular philosophy around keeping calculators separate is sound thinking

The Big One: Missing Reference Files and Templates

The framework mentions three specific templates (driver sheet, sensitivity table, executive summary) but doesn't actually provide them. This is your biggest bang-for-buck fix. Right now, when someone tries to use this skill, they get a conceptual outline without the concrete tools to execute it.

Here's the fix: Create references/ directory with:

• driver-sheet-template.md – Shows the actual structure: Base Metrics tab (member count, transaction frequency, AOV, churn, CAC), tier structure columns, rewards cost breakdown
• sensitivity-analysis-template.md – Example showing how to vary one input (say, churn rate ±20%) and track impact on model outputs
• executive-summary-template.md – Approval-ready format with key assumptions, outcomes, financial impact

This alone would bump you +5 points and move Utility from 11 to 16. Massive difference.

Other Things Worth Fixing

1. Description lacks trigger phrases – Right now it's "Use to model economics..." which won't activate in searches. Add specific triggers: "Use when asked to 'forecast loyalty ROI', 'model point economics', 'calculate loyalty breakage', or 'design tier benefits'" (+2 points)

2. No validation or feedback loops – Add a section showing how to verify the model: "Cross-check point liability against finance actuals. Stress-test with ±20% variance on key inputs. Review assumptions with stakeholders." This transforms it from theory to practice (+3 points)

3. Framework steps need more verb forms – "Gather Inputs" instead of just "Inputs—member base..." makes it actionable. Same with "Calculate Tier Economics" vs just listing components (+2 points)

4. Missing concrete example – One scenario walk-through (100K members, $50 AOV, 5% churn) with actual output numbers would show how the pieces fit together (+2 points)

Quick Wins (in order of impact)

• Create reference templates for driver sheet, sensitivity analysis, and executive summary (+5 points)
• Add trigger phrases to description (+2 points)
• Include validation/feedback loop section (+3 points)
• One worked example scenario (+2 points)

These four moves get you from 64 to about 76, solid C territory—more importantly, your skill becomes actually usable instead of just conceptual.

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