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heleni-whatsapp

Tracks unanswered WhatsApp messages and maintains per-conversation memory for OpenClaw agents.

5|1|Updated Apr 1, 2026
Search Tags:#automation#context#memory#inbox#whatsapp#dedup#openclaw
One-click install
npx skills add https://github.com/netanel-abergel/pa-skills --skill heleni-whatsapp
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: heleni-whatsapp
Source: https://github.com/netanel-abergel/pa-skills/tree/main/skills/heleni-whatsapp
Command: npx skills add https://github.com/netanel-abergel/pa-skills --skill heleni-whatsapp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill centralizes per-conversation memory for OpenClaw WhatsApp agents and tracks unanswered messages, reducing duplication and ensuring context persists across DMs and groups.

Core Features & Use Cases

  • Per-conversation memory folders for groups and direct messages with structured context, decisions, and notes.
  • Unanswered message inbox tracking to surface pending replies and maintain responsiveness.
  • Dedup prevention and strict context isolation to avoid cross-chat leakage and repeated notes.
  • Mandatory context updates after significant exchanges to keep memory in sync with actions and decisions.

Quick Start

Initialize memory for a DM or group and begin logging conversations immediately.

Frequently Asked Questions about heleni-whatsapp

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

FAQPage Schema
How do I maintain per-conversation memory for WhatsApp automation agents?▼

Per-conversation memory is maintained by creating structured folders for groups and direct messages, logging context and decisions, and enforcing mandatory memory updates after significant exchanges to keep agent memory synchronized.

How does an unanswered WhatsApp message inbox work for agents?▼

An unanswered message inbox tracks pending replies across multiple personal assistants by performing lightweight heartbeat checks, surfacing messages that require responses to maintain chat responsiveness and prevent dropped conversations.

Can I prevent duplicate context when automating WhatsApp group chats and direct messages?▼

Yes, dedup prevention and strict context isolation are applied to both group chats and direct messages, preventing cross-chat leakage and avoiding repeated notes within the same conversation memory directories.

Does WhatsApp agent memory work with a database fallback when file-based storage is not enough?▼

Yes, the file-based memory system supports an optional database fallback when PA_DB_URL is available, allowing per-conversation memory and inbox tracking to scale beyond local file directories.

What is the best way to track context across multiple WhatsApp agents without losing conversation history?▼

Centralizing per-conversation memory with structured directories and heartbeat inbox checks ensures context persists across multiple personal assistants, reducing duplication and tracking unanswered messages for both DMs and groups.

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