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Zernio Comment To Dm

Community
Enriquemarq1
zernio-comment-to-dm

Build Instagram/Facebook comment-to-DM automations through the Zernio API on command. Tell Claude a post, a keyword, and the message — Claude creates the comment automation (and orchestrates a short follow-up DM "sequence") via Zernio, so you never click through a dashboard or clone workflows. Reuse it for any new post or keyword in seconds. Triggers on: "set up a comment to DM", "new keyword automation", "when someone comments X DM them", "build a comment trigger", "make a Zernio comment automation", "comment-to-DM sequence".

Overview

PublisherEnriquemarq1
Repositoryzernio-library-skills
Skill namezernio-comment-to-dm
Stars
50
Forks
13
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

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

  • Open source

    Published by Enriquemarq1 on GitHub. Read the source before you install it.

Installation

Install the Zernio Comment To Dm 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.
    https://github.com/Enriquemarq1/zernio-library-skills/tree/main/.claude/skills/zernio-comment-to-dm
  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/Enriquemarq1/zernio-library-skills.git /tmp/zernio-library-skills
mkdir -p .claude/skills
cp -r /tmp/zernio-library-skills/.claude/skills/zernio-comment-to-dm .claude/skills/zernio-comment-to-dm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Zernio Comment To Dm 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 Zernio Comment To Dm 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 Zernio Comment To Dm 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.

zernio-comment-to-dm

Turn a comment section into captured leads. When someone comments your keyword on a post, Zernio auto-DMs them — and this skill lets you set that up just by asking Claude, for any post or keyword, in seconds. No dashboard clicking, no cloning workflows.

Want this inside your own app, for every client, with a builder and live activity? See white-label-automations and the Automations tab in apps/white-label-app/.

The skill informs; the agent acts. This file gives Claude the Zernio API contract + the recipe. Claude executes with curl (or the user's HTTP tool). Always confirm with the user before creating/activating an automation (it goes live on a real audience).

What you can ask

  • "When someone comments GUIDE on my latest post, DM them my free template link."
  • "New automation: post <id>, keyword PRICING, DM the pricing + ask if they want a call."
  • "Pause / update / delete the GUIDE automation."
  • "Walk a short sequence: DM them the resource, then if they reply, ask for their email."

What Claude needs (ask the user once, then remember in-session)

  1. ZERNIO_API_KEY — Authorization: Bearer <key> (zernio.com → Settings → API keys).
  2. profileId + accountId — the Zernio profile + connected IG/FB account (GET /profiles, GET /accounts if unknown).
  3. platformPostId — the post the automation watches (the IG/FB post ID).
  4. keyword(s), the DM message, optional public comment reply.

The recipe (Claude follows this)

1. Create the comment automation (the core — native, one call)

bash
curl -s -X POST "https://zernio.com/api/v1/automations" \
  -H "Authorization: Bearer $ZERNIO_API_KEY" -H "Content-Type: application/json" \
  -d '{
    "profileId": "<profileId>",
    "accountId": "<accountId>",
    "platformPostId": "<platformPostId>",
    "name": "GUIDE — free template",
    "keywords": "GUIDE",
    "dmMessage": "Hey! Here is the free template you asked for 👇 [link]. Want me to walk you through it?",
    "commentReply": "Check your DMs 📩",
    "isActive": true
  }'

Returns the automation id. From now on, every comment matching the keyword auto-DMs.

2. Reuse for a NEW post / keyword (the whole point)

Just change platformPostId, keywords, name, dmMessage and POST again. Claude can do this from one sentence — "same thing but keyword PRICING on post , DM the pricing." No cloning, no dashboard. Manage them: GET /automations, PUT /automations/{id} (pause via isActive:false), DELETE /automations/{id}, logs via GET /automations/{id}/logs?status=sent.

3. The "sequence" (follow-up DMs — Claude-orchestrated)

Zernio's automation sends ONE DM per matching comment (no native multi-step sequence). For a real sequence, the host app/agent watches the conversation and sends follow-ups:

  • New replies arrive via the inbox (GET /inbox/conversations, GET /inbox/messages/{conversationId}).
  • Send the next step: POST /inbox/send { "conversationId", "accountId", "message" }.
  • e.g. step 1 = the resource (the automation's dmMessage), step 2 (after they reply) = "great — what's the best email to send the full thing to?", step 3 = deliver + confirm. Claude composes each step in the creator's voice; keep it short, one ask at a time.

Guardrails

  • Confirm before going live. Show the user the keyword + DM + reply, get a yes, then POST.
  • Never print the API key. It lives in env/the user's secret store.
  • One keyword per automation (keeps it intentional); create separate automations for separate keywords/posts.
  • Voice: warm, direct, human, no spam. The DM should sound like the creator.

Reference

  • reference/zernio-automations-api.md — full endpoint contract (verified from docs.zernio.com).
  • templates/automation.json — copy-paste body for a new comment automation.

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 Zernio Comment To Dm AI skill do?

Build Instagram/Facebook comment-to-DM automations through the Zernio API on command. Tell Claude a post, a keyword, and the message — Claude creates the comment automation (and orchestrates a short follow-up DM "sequence") via Zernio, so you never click through a dashboard or clone workflows. Reuse it for any new post or keyword in seconds. Triggers on: "set up a comment to DM", "new keyword automation", "when someone comments X DM them", "build a comment trigger", "make a Zernio comment automation", "comment-to-DM sequence".

Why use Zernio Comment To Dm on TypingMind?

Because you install it once and use it with any model. Zernio Comment To Dm 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 Zernio Comment To Dm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Enriquemarq1/zernio-library-skills/tree/main/.claude/skills/zernio-comment-to-dm. 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 Zernio Comment To Dm?

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 Zernio Comment To Dm?

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

Is the Zernio Comment To Dm AI skill free?

Yes. It is published on GitHub by Enriquemarq1 under the MIT license. 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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