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Whatsapp Evo

Community
antoniolg
whatsapp-evo

Manage WhatsApp via Evolution API (v2.x): list chats with unread messages and reply.

Overview

Publisherantoniolg
Repositoryagent-kit
Skill namewhatsapp-evo
Stars
97
Forks
16
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by antoniolg on GitHub. Read the source before you install it.

Installation

Install the Whatsapp Evo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/antoniolg/agent-kit.git /tmp/agent-kit
mkdir -p .claude/skills
cp -r /tmp/agent-kit/skills/whatsapp-evo .claude/skills/whatsapp-evo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Whatsapp Evo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Whatsapp Evo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Whatsapp Evo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

WhatsApp (Evolution API)

Requirements

  • Environment variables:
    • EVOLUTION_API_URL (optional if config)
    • EVOLUTION_API_TOKEN
    • EVOLUTION_INSTANCE (optional if config)
  • Configure api_url and instance in ~/.config/skills/config.json under whatsapp_evo (recommended). The token must be set via env var.

Example:

json
{
  "whatsapp_evo": {
    "api_url": "https://evo.example.com",
    "instance": "MyInstance"
  }
}

Commands (from the skill folder)

1) Inbox (unread)

scripts/whatsapp-inbox --json-out /tmp/whatsapp-inbox.json
  • Shows a clean numbered list.
  • Saves metadata for later actions.
  • Note: the inbox is computed from the last incoming message without READ status in the API (it may not match "mark as unread" in the app).
  • Saves local state in ~/.cache/whatsapp-evo/inbox-state.json to avoid repeating chats (override with --state or WHATSAPP_EVO_STATE_PATH).
  • Use --no-update-state if you want to list the same chats again.
  • Use --since-days N to ignore old messages in the first pass (default 7).
  • Use --pending-reply to list conversations from the last N days where the latest message is not yours (ignores local state).

2) Reply (with user confirmation)

scripts/whatsapp-reply --index <n> --text "reply"
  • Replies to the chat at the given index using message/sendText.
  • For direct chats use the number; for groups use remote_jid if needed.
  • Optional: --delay <ms>, --link-preview, --instance, --url.

3) Conversation history

scripts/whatsapp-history --index <n> --limit 50
  • Use --jid or --number if you don’t have an index.
  • Filter by date with --since 2025-01-01 or --since 2025-01-01T10:00:00Z and --until.
  • Use --incoming-only to show only inbound messages.

Metadata format

/tmp/whatsapp-inbox.json contains:

  • index
  • name
  • remote_jid
  • number
  • unread_count
  • last_message_id
  • last_message_from_me
  • last_message_text
  • last_message_timestamp
  • last_message_sender

Rules

  • Show the user only the clean list; never show tokens.
  • Before replying, ask for confirmation.
  • If the JSON is stale or missing, re-run inbox.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Whatsapp Evo AI skill do?

Manage WhatsApp via Evolution API (v2.x): list chats with unread messages and reply.

Why use Whatsapp Evo on TypingMind?

Because you install it once and use it with any model. Whatsapp Evo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Whatsapp Evo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/antoniolg/agent-kit/tree/main/skills/whatsapp-evo. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Whatsapp Evo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Whatsapp Evo?

As many as you like. As long as a model supports skills, you can use Whatsapp Evo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Whatsapp Evo AI skill free?

It is published on GitHub by antoniolg. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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