whatsapp-sync

whatsapp-sync is an agent for coding agents from datacore-one/datacore. It costs 0 tokens per session (1,068 once invoked), scanned A, original, MIT.

An agent that copies contacts and recent conversations from WhatsApp through the WAHA gateway into a CRM. WAHA is a service that connects software to an active WhatsApp session.

In plain words
What is it for?
Use it to sync WhatsApp contacts, collect recent interactions, and maintain phone-number-to-contact links.
Why use it?
It removes the need to copy WhatsApp contacts and interaction history into a CRM by hand.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/datacore-one/datacore/whatsapp-sync
Clone the repo
git clone --depth 1 https://github.com/datacore-one/datacore

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for whatsapp-sync

README.md
[![agentmods](https://agentmods.dev/badge/agents/datacore-one/datacore/whatsapp-sync.svg)](https://agentmods.dev/agents/datacore-one/datacore/whatsapp-sync)
Your own site
<a href="https://agentmods.dev/agents/datacore-one/datacore/whatsapp-sync"><img src="https://agentmods.dev/badge/agents/datacore-one/datacore/whatsapp-sync.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,068 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01068
Opus 5 $0.00000 $0.00534
Sonnet 5 $0.00000 $0.00214
Haiku 4.5 $0.00000 $0.00107

Measured yesterday against content hash 6d8c1769d4c5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

whatsapp-sync scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.datacore/modules/whatsapp/agents/whatsapp-sync.md · 197 lines

How it starts

The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.

whatsapp-sync Agent

Synchronize contacts and interactions from WAHA WhatsApp gateway.

Engram Injection

Before starting work, load relevant learned patterns:

  1. Preferred: Call plur_admin MCP tool with action = "plur_inject_hybrid", prompt = your task description, scope = agent:whatsapp-sync
  2. Fallback: If MCP is unavailable, read .datacore/state/agent-engrams/whatsapp-sync.md for compiled engrams

Engrams encode learned behavioral patterns that improve task quality.

Purpose

Real-time synchronization with WhatsApp via WAHA gateway:

  1. Sync contacts from WhatsApp contact list
  2. Extract recent interactions for CRM
  3. Maintain phone-to-contact mapping

Prerequisites

  • WAHA gateway running (docker run devlikeapro/waha)
  • Active WhatsApp session (QR code scanned)
  • Session status: WORKING

Trigger

  • Manual via /whatsapp sync
  • Scheduled (if configured)
  • After gateway reconnection

Workflow

1. Check Session

from lib import WAHAClient, SessionStatus

client = WAHAClient("http://localhost:3000")
status = await client.get_session_status()

if status != SessionStatus.WORKING:
    print(f"Session not active: {status.value}")
    return

2. Sync Contacts

# Get contacts from WhatsApp
contacts = await client.get_contacts()

for contact in contacts:
    # Check if exists in CRM
    existing = find_contact_by_phone(contact.phone)

    if not existing:
        # Create new contact
        create_crm_contact(contact)
    else:
        # Update phone index
        update_phone_index(contact.phone, existing.name)

3. Sync Recent Chats

# Get recent chats
chats = await client.get_chats(limit=50)

for chat in chats:
    if chat.is_group:
        continue  # Skip groups for now

    # Get recent messages
    messages = await client.get_chat_messages(chat.id, limit=20)

    # Extract interactions
    for msg in messages:
        log_interaction(chat, msg)

Read the full file on GitHub · 197 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 197 lines · 0 tokens per session scan A 6d8c1769d4c5

Subscribe to this mod's changes

whatsapp-sync is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,068 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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