Comment Generator Skill

Overview

Supply the target post type (text or picture) along with an optional tone selection and an emoji toggle. The response returns an array containing generated comment strings matching the requested tone, which defaults to positive. The Free tier generates one comment per request, while paid plans can specify a count of up to 10.

Live Test Comment Generator Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as CommentGeneratorSkill. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

{
  "name": "CommentGeneratorSkill",
  "arguments": {
    "mode": "text"
  }
}

You do not name the tool yourself; the model picks it. Asking about text in the terms this skill covers is enough for it to reach for CommentGeneratorSkill on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every skill in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervekit": {
      "url": "https://api.vervekit.com/v1/mcp"
    }
  }
}

https://api.vervekit.com/v1/mcp

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

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{
  "status": "ok",
  "error": null,
  "data": {
    "count": 5,
    "mode": "text",
    "tone": "positive",
    "comments": [
      "You're so right! is a game-changer Wow! 😍",
      "Inspiring stuff gives me all the feels Wow! ✨",
      "Thanks for sharing this gives me all the feels Perfect! 💯",
      "Exactly my thoughts is on fire Wow beyond! 🌟",
      "Great outlook in everything here, very bright! slays! For sure! 😊"
    ]
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

A call costs 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Social Feed Automation

Social media management apps generate quick draft replies in positive or neutral tones to speed up community manager workflows across image feeds.

Synthetic Dataset Creation

Machine learning teams produce labeled positive and negative social comments to train and test text sentiment classification algorithms.

Forum Prototype Seeding

When staging new social applications, developers populate mock feed discussions with sample image-post comments instead of manually writing placeholder copy.

Moderation Bot Benchmarking

Evaluate automated content filters by testing incoming negative comment responses against keyword rules and toxicity thresholds before deploying to production.

Other ways to use Comment Generator Skill

Set up Comment Generator Skill on VerveKit, or reach the same source a different way. Your VerveKit account and credits work on all of them — one key, one balance.

Related

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