conversion-diagnostic-kit
Structured approach for investigating funnel issues across e-commerce experiences.
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Installation for Agentic Skill
View all platforms →skilz install gtmagents/gtm-agents/conversion-diagnostic-kitskilz install gtmagents/gtm-agents/conversion-diagnostic-kit --agent opencodeskilz install gtmagents/gtm-agents/conversion-diagnostic-kit --agent codexskilz install gtmagents/gtm-agents/conversion-diagnostic-kit --agent geminiFirst time? Install Skilz: pip install skilz
Works with 22+ AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/gtmagents/gtm-agentscp -r gtm-agents/plugins/e-commerce/skills/conversion-diagnostic-kit ~/.claude/skills/Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Repository
- gtm-agents
- Stars
- 31
- Forks
- 7
- Type
- Non-Technical
- Meta-Domain
- development
- Primary Domain
- github
- Market Score
- 28
Agent Skill Grade
D Score: 66/100 Click to see breakdown
Score Breakdown
Areas to Improve
- Description needs trigger phrases
- Missing Reference Files for Templates
- Vague Description Missing Triggers
Recommendations
- Focus on improving Utility (currently 11/20)
- Address 3 high-severity issues first
- Add trigger phrases to description for discoverability
Graded: 2026-01-24
Developer Feedback
I've been digging into conversion optimization toolkits, and your diagnostic approach is interesting—though the execution feels like it's caught between being a reference guide and an interactive tool. What's the vision here: is this meant to help developers understand conversion problems or solve them?
Links:
The TL;DR
You're at 66/100, solidly in D territory. This is based on Anthropic's progressive disclosure architecture standards for agentic skills. Your strongest area is spec compliance (11/15)—the frontmatter is clean. Your weakest is utility (11/20)—the framework describes what to do but doesn't actually enable developers to do it.
What's Working Well
- Valid YAML frontmatter - Name follows conventions perfectly, and the structure is technically sound
- Consistent terminology - "Signal Stack," "Segmentation Grid," "Conversion Taxonomy"—you're building a coherent mental model
- Real-world focus - You're tackling an actual gap (conversion diagnostics), not solving problems that don't exist
The Big One: Missing Templates & Reference Files
Here's what's eating 6+ points: you mention three templates (workbook, standup agenda, experiment brief) but don't actually provide them. This kills your utility score because developers are left saying, "okay, how do I structure this stuff?"
Fix: Create a references/ directory with actual files:
references/templates/diagnostic-workbook.md- Data inputs, findings capture formatreferences/templates/standup-agenda.md- Cross-functional war room structurereferences/templates/experiment-brief.md- Hypothesis, KPIs, guardrails template
Even stub templates would add 6 points because they shift this ...
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