Convert analytics dashboard JSON into prioritized operational recommendations.
npx skills add https://github.com/acrid-auto/acrid-brain --skill analytics-acrid-auto
Please help me install this Agent Skill. Skill: analytics Source: https://github.com/acrid-auto/acrid-brain/tree/main/skills/analytics Command: npx skills add https://github.com/acrid-auto/acrid-brain --skill analytics-acrid-auto
This Skill converts raw analytics data into prioritized, actionable recommendations so Acrid can make data-driven decisions instead of relying on intuition.
Analyze memory/analytics-dashboard.json, verify freshness, and output a three-line summary of traffic, revenue, and content with one prioritized recommendation.
High-intent search queries and answers about installing and using this skill.
To convert raw dashboard metrics into operational recommendations, supply a recent consolidated analytics dashboard JSON. The system verifies API success, flags anomalies, and outputs prioritized next actions with expected impact for website, revenue, and content data.
Detecting anomalies in website traffic and revenue analytics requires providing a consolidated dashboard JSON. The system reads this data to flag traffic spikes, new revenue events, and API failures, then summarizes the findings for operational review.
Automated operational insight generation is the process of reading consolidated analytics dashboard JSON to flag anomalies and summarize key metrics. It converts raw traffic, revenue, and content data into prioritized, specific recommendations for data-driven decision making.
Yes, you need a recent consolidated analytics dashboard JSON file to analyze metrics and generate recommendations. The system requires this input to verify API success, flag anomalies, and produce operational recommendations conforming to its specific output rubric.
Yes, you can use analytics data to update the ops cockpit scoreboard during session checks. The system reads dashboard JSON for session-start checks and /ops runs, producing specific next actions with expected impact to update the scoreboard.
A limitation of relying on analytics dashboards for operational decisions is the strict requirement for recent dashboard JSON and API success verification. Without fresh, consolidated input data, the system cannot accurately flag anomalies or generate prioritized recommendations.
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