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pulse-weekly

Aggregate Discord and WhatsApp activity into a weekly HTML community analysis report.

520|175|Updated Apr 8, 2026
Search Tags:#discord#whatsapp#product insights#community analytics#sentiment trends#weekly reporting
One-click install
npx skills add https://github.com/evolution-foundation/evo-nexus --skill pulse-weekly-evolution-foundation
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pulse-weekly
Source: https://github.com/evolution-foundation/evo-nexus/tree/main/.claude/skills/pulse-weekly
Command: npx skills add https://github.com/evolution-foundation/evo-nexus --skill pulse-weekly-evolution-foundation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It eliminates the manual effort of summarizing community activity by aggregating Discord and WhatsApp signals into one structured weekly report that highlights engagement, sentiment, contributions, and product/documentation gaps.

Core Features & Use Cases

  • Weekly aggregation (Discord + WhatsApp): Collects messages from the last 7 days from specified Discord channels and WhatsApp sources to build a unified view of activity.
  • Engagement and support metrics: Computes WAM, growth/churn indicators, communicator rate, resolution rate, first response time, and messages per active member.
  • Sentiment, topics, and actionable insights: Detects sentiment trends and top discussion topics, then surfaces top contributors, new contributors, churn risk candidates, and product/docs backlog items.
  • Comparison vs previous week: When prior reports exist, compares key metrics and trends to show week-over-week changes.

Quick Start

Ask the AI to generate the weekly community analysis report (e.g., "weekly community analysis") so it fetches the last 7 days of Discord/WhatsApp activity, computes metrics, and saves the HTML report to the weekly reports folder.

Frequently Asked Questions about pulse-weekly

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate weekly community reporting for Discord and WhatsApp activity?▼

Weekly community reporting is automated by aggregating Discord and WhatsApp messages from the last 7 days, computing engagement metrics like WAM and resolution rate, and generating an HTML report. This eliminates manual summarization by unifying activity signals into actionable insights.

What community engagement metrics can I track in a weekly Discord and WhatsApp report?▼

Weekly Discord and WhatsApp reports track WAM, growth and churn indicators, communicator rate, resolution rate, first response time, and messages per active member. The analysis also detects sentiment trends, top discussion topics, and highlights top contributors and churn risk candidates.

Can I compare current community engagement metrics against the previous week?▼

Yes, week-over-week comparison is supported when prior reports exist. The analysis compares key metrics and sentiment trends from the current 7-day period against the previous week to highlight changes in Discord and WhatsApp community engagement and support performance.

Does the weekly community analysis identify product and documentation gaps?▼

Yes, the weekly community analysis identifies product and documentation gaps by consolidating Discord and WhatsApp chatter. It surfaces backlog items and support resolution performance alongside sentiment trends to help teams pinpoint where documentation or product improvements are needed.

How do I generate an HTML report from Discord and WhatsApp messages?▼

To generate an HTML report, the skill collects 7 days of Discord and WhatsApp messages, computes deterministic metrics, and applies an HTML template. The resulting report file is saved to the weekly reports folder, ready for weekly review cycles.

What's the best way to track contributor highlights across Discord and WhatsApp?▼

Tracking contributor highlights is handled by aggregating Discord and WhatsApp activity to surface top contributors, new contributors, and churn risk candidates. The analysis computes engagement metrics and sentiment trends to provide a structured weekly view of community participation.

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