AI Agent Hub
Back to skills
Fun Gameplay Revenue Weekly Report Automation icon

Fun Gameplay Revenue Weekly Report Automation

Development Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Please follow https://skillhub.cn/install/skillhub.md and install @user_9775ba75/dp-qianghuaban.

About this skill

What Problem It Solves

This skill targets weekly revenue reporting workflows where data arrives from backend CSV files, Excel email tables, and gameplay planning sheets. It splits the process into four stages: data cleaning, metric calculation, attribution analysis, and compliance validation. Each stage has a narrow responsibility, which helps avoid accidental changes to raw fields, templates, and business definitions.

Core Capabilities and Key Steps

  • Data cleaning: Reads backend_template_data.csv, backend_data_table.csv, fun_gameplay_email_table.xlsx, and gameplay_group_planning_timeline.xlsx, filters rows by a user-defined 14-day window, removes blank or invalid rows, and aligns dates across files.
  • Metric calculation: Computes weekly and non-activity metrics such as total fun revenue, delayed fun, instant fun, 100% deposit, withdrawal consumption, and total users, then aggregates gameplay deposit structure by wanfa_type.
  • Attribution analysis: Outputs a fixed-template analysis covering time trends, gameplay mix, user tiers, activity impact, abnormal events, and overall summary.
  • Compliance validation: Checks heading structure, table 1/table 2 layouts, week-over-week formulas, units, the relationship total fun revenue ≈ delayed fun + instant fun, and required warnings when absolute week-over-week change exceeds 50%.

Boundaries and Caveats

It fits stable reporting environments where source tables already contain dt or date columns and the weekly template rarely changes. If field names, sheet names, or gameplay categories change, input conventions must be updated. The skill does not invent free-form business narratives or replace analyst judgment; abnormal fluctuations are flagged for confirmation by operations, data, or product teams.

Use Cases

  • Extract 14-day data from backend CSV files and email Excel sheets, normalize dates, and remove invalid rows.
  • Compute weekly and non-activity metrics for fun revenue, deposits, withdrawals, and users, then build week-over-week tables.
  • Produce a template-compliant revenue weekly report with time, gameplay, user-tier, and anomaly attribution analysis.
  • Validate heading structure, table layouts, week-over-week formulas, units, and required anomaly flags before publishing.

Best For

  • Data operations staff who consolidate backend tables and email sheets into a fixed revenue weekly report
  • Business analysts who calculate deposits, withdrawals, fun revenue, and week-over-week metrics under stable definitions
  • Operations or product staff who review gameplay campaigns and produce attribution conclusions
  • Reviewers who check report templates, table structures, units, and data formulas before release