instrumentation

I was looking at how you've structured the instrumentation hooks—the pattern of intercepting execution flow without bloating the core logic is solid, but the progressive disclosure could use some work to handle the complexity better.

Links:

• GitHub
• Your agentic skill in the SkillzWave marketplace

The TL;DR

You're at 73/100, solidly in C territory. This is based on Anthropic's Claude Skills best practices. Your Spec Compliance is your strongest pillar (12/15)—the frontmatter and naming conventions are spot-on. Where you're losing points: Utility (12/20) and Progressive Disclosure (22/30). The skill reads more like a checklist than a usable framework.

What's Working Well

• Spec compliance is tight – Your frontmatter is valid YAML, naming follows conventions perfectly, and the overall structure is clean.
• Consistent terminology – "Events," "properties," "tracking plan," "data contract"—you've nailed consistency throughout. Developers won't get confused by switching between terms.
• Real problem domain – You're addressing actual analytics instrumentation pain points. The framework acknowledges governance, validation, and observability—that's not obvious stuff.

The Big One: Missing Templates & Examples

This is your main blocker. You mention templates everywhere—tracking plan sheet, data contract checklist, observability runbook—but they don't exist as reference files. You also say "pair each event with sample payloads" but provide zero examples.

Why this matters: Developers using this skill need concrete starting points, not just concepts. Right now they're building the entire template from scratch.

The fix: Create three reference files:

• references/tracking-plan-template.md – A filled-in example showing ...