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Skillzwave

revenue-health-dashboard

31 stars 7 forks
28
D

Visualization blueprint for revenue KPIs, guardrails, and action callouts.

Marketplace

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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skilz install gtmagents/gtm-agents/revenue-health-dashboard
skilz install gtmagents/gtm-agents/revenue-health-dashboard --agent opencode
skilz install gtmagents/gtm-agents/revenue-health-dashboard --agent codex
skilz install gtmagents/gtm-agents/revenue-health-dashboard --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/gtmagents/gtm-agents
2. Copy the agent skill directory:
cp -r gtm-agents/plugins/revenue-analytics/skills/revenue-health-dashboard ~/.claude/skills/
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Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

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Agentic Skill Details

Owner
gtmagents (GitHub)
Repository
gtm-agents
Stars
31
Forks
7
Type
Technical
Meta-Domain
data ai
Primary Domain
data analysis
Market Score
28
Agentic Skill Grades →

Agent Skill Grade

D
Score: 62/100 Click to see breakdown

Score Breakdown

Spec Compliance
11/15
PDA Architecture
18/30
Ease of Use
14/25
Writing Style
7/10
Utility
11/20
Modifiers: +1

Areas to Improve

  • Description needs trigger phrases
  • Missing reference files for progressive disclosure
  • Generic trigger terms in description

Recommendations

  • Focus on improving Ease Of Use (currently 14/25)
  • Focus on improving Utility (currently 11/20)
  • Address 3 high-severity issues first

Graded: 2026-01-24

Developer Feedback

I've been digging into financial dashboarding skills lately, and I noticed your revenue-health-dashboard takes a pretty opinionated approach to metrics visualization—curious what drove some of those architectural choices, especially given the D-grade landing on utility and polish.

Links:

The TL;DR

You're at 62/100, solidly in D territory. The grading is based on Anthropic's best practices for agentic skills—progressive disclosure, ease of use, spec compliance, writing clarity, and real-world utility. Your Spec Compliance is decent (11/15), but Utility (11/20) and Progressive Disclosure Architecture (18/30) are dragging the score down. Basically, the framework is there conceptually, but it lacks the scaffolding and actionable depth to actually guide someone through building this.

What's Working Well

  • Spec-compliant frontmatter – Your YAML structure is clean and valid; the hyphen-case naming follows conventions perfectly
  • Clear conceptual framework – The KPI Stack, Segmentation Layer, and Guardrail components make intuitive sense for revenue dashboards
  • Relevant terminology consistency – You stick with KPIs, guardrails, and dashboard language throughout, which keeps things cohesive
  • Real use cases – The tips section acknowledges practical needs like snapshot-before-remediation tracking

The Big One: Missing Progressive Disclosure Architecture

Here's the thing: you've got 31 lines of content crammed into a single SKILL.md file with zero reference structure. For a dashboard skill, that's leaving a ton of value on the table.

Why it matters: Developers need progressive disclosure—give them the quick framework first, then let them drill down into spe...

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