Works with the AI tools you already use
Live Operations Dashboard Reference Pack
Design structured operations dashboards with metric source mapping and live-vs-static data classification.
Secure checkout via Stripe
See it in action
You say
I need to plan a dashboard for my agency. We track revenue in Stripe, leads in Hubspot, and content stats in a Google Sheet. Some data is manual. Help me map the sources and layout.
Your agent does
Dashboard status: DASHBOARD_PLAN_READY Type: REFRESHABLE_DASHBOARD Source Map:
- MRR: Stripe (Live Connector)
- New Leads: Hubspot (Refreshable)
- Content Views: Sheets (Static Export)
Layout: Top KPI row followed by Revenue/Pipeline sections. Data gap: Newsletter stats missing.
What you get
About this skill
The problem
Business dashboards fail when live API data is mixed with static manual exports without clear labels. Founders and operators often struggle with fragmented metrics across Stripe, CRMs, and spreadsheets, leading to unverified numbers and stale reports.
What it does
- Builds a structured dashboard scaffold across revenue, pipeline, marketing, and support.
- Maps every metric to its primary source while classifying it as live, refreshable, or static.
- Generates a data gap register to highlight missing connectors or stale information.
- Produces an executive summary structure and a validation checklist for human review.
- Creates a repeatable reporting workflow with a mandatory final receipt.
Frameworks & tools
Designed for data from Stripe, CRM platforms, Notion, Slack, Google Workspace, and email marketing tools.
Why this beats prompting it yourself
This skill enforces a strict operating procedure that separates verified data from assumptions. It prevents the common pitfall of treating LLM-generated placeholders as real-time business intelligence by requiring source mapping and refresh cadence notes.
Use cases
- Designing a weekly founder review dashboard for revenue and pipeline tracking.
- Mapping agency client operations across multiple marketing and social platforms.
- Identifying data gaps and connector requirements before building a formal BI tool.
- Structuring executive summaries for monthly leadership business reviews.
Known limitations
Does not provide actual data engineering, real-time API connectors, or automated financial decision-making capabilities.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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