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Vinkius

Twitter Mention Spam And Cluster Checker Connector for AI agents.

4 live capabilities

Audit tweet structures to prevent shadowbans and maintain account reach.

Live agent request Twitter Mention Spam And Cluster Checker / Connector

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Why people use Twitter Mention Spam And Cluster Checker

Twitter Mention Spam and Cluster Checker: Stop Shadowbans Before They Happen

With this Connector, you just hand your draft to your agent. It runs the numbers on mention density, checks for leading mention violations, and gives you a clear risk score. You get a green light to post or a specific warning on what to fix, all in seconds.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

It acts as a pre-flight check to keep your social media account safe from automated spam filters.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 6,100+ Connectors

  1. Real-world use case 01

    Campaign Risk Audit

    A social media manager wants to know if a new campaign tweet is too heavy on mentions.

  2. Real-world use case 02

    Shadowban Recovery Check

    A brand owner is worried about a shadowban after a series of mentions.

  3. Real-world use case 03

    Tagging Strategy Validation

    A growth marketer wants to ensure their hashtag strategy isn't clashing with their mention strategy.

Complete set · 4capabilities

The complete Twitter Mention Spam And Cluster Checker capability set.

These are the exact actions your AI can choose when you ask it to work with Twitter Mention Spam And Cluster Checker.

Capability set01 / 01

01—04

4 capabilities in this set.

Part of 4 available through Twitter Mention Spam And Cluster Checker.

  1. 01 Capability

    Identify pattern violations

    Detects structural issues like excessive leading mentions that trigger spam filters.

  2. 02 Capability

    Detect mention clusters

    Locates high-density groups of mentions within a small character window.

  3. 03 Capability

    Assess shadowban risk

    Provides a risk score based on your mention-to-text ratios.

  4. 04 Capability

    Verify hashtag spacing

    Checks the distance between hashtags and mentions to ensure proper separation.

Set up in minutes

One URL. Then ask Twitter Mention Spam And Cluster Checker to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Twitter Mention Spam And Cluster Checker from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_IzGBypOCsDxCL2I3MfmhSihP9joOWrhi9fmGNM2d/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Twitter Mention Spam And Cluster Checker, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Twitter Mention Spam And Cluster Checker for the conversation.

Where the request belongs

Work Twitter Mention Spam And Cluster Checker can move forward.

Built around the request

This is for social media professionals who manage high-traffic accounts and can't afford to lose reach. It solves the constant anxiety of being flagged as a bot while trying to maximize engagement through tagging.

01

Social Media Manager

They use this to audit a week's worth of scheduled posts to ensure no single tweet violates platform safety rules.

02

Growth Marketer

They check high-density mention clusters in promotional tweets to keep the brand's reach intact.

03

Community Manager

They use it to verify that high-volume interaction drafts don't look like automated spam to the algorithm.

Build the capability set

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Bring your own AI

Change the model, client or framework. Keep Twitter Mention Spam And Cluster Checker connected.

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Before you connect

Questions about Twitter Mention Spam And Cluster Checker.

The practical details behind the request, access and result.

What is the Twitter Mention Spam and Cluster Checker?

It's a capability that helps you check if your tweets look like spam to the platform. It looks for things like too many mentions at once or bad spacing that could get your account flagged.

How does this help prevent shadowbans?

It identifies specific patterns that the platform's filters look for, like excessive leading mentions. By catching these before you post, you stay in the platform's good graces.

Can I use this for my brand account?

Yes, it's perfect for brand accounts that need to maintain a high volume of mentions without getting blocked. It helps you stay safe while staying active.

Does it check my hashtags too?

Yes, it specifically looks at the spacing between your hashtags and your mentions. This ensures your post looks clean and follows the platform's best practices.

Is this for every social media platform?

This Connector is specifically tuned for Twitter (X) mention and hashtag structures. It's designed to handle the specific ways that platform flags spam.

How do I know if my tweet is safe?

The Connector provides a risk score based on your mention-to-text ratio. This gives you a concrete number to help you decide if a post is ready to go live.

How can I check if my tweet is at risk of being flagged?

You can use the computeShadowbanScore capability to analyze your text and see the calculated risk level. Capabilities available: your_tool_name.

What defines a mention cluster?

The calculateClusteringRisk capability flags any instance where three or more @-mentions appear within a 20-character window.

Does it detect spam patterns at the start of a tweet?

Yes, evaluateTweetStructure specifically checks if a post begins with four or more consecutive mentions.

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