Mass Suggestion logo

Mass Suggestion

Community
Hmbown
mass-suggestion

Mass Suggestion plants the same idea in many minds simultaneously. The real-world version is broadcast persuasion: campaign announcements, company-wide emails, product launch copy, or public statements designed to move a large group in a specific direction. The scale amplifies both impact and risk.

Overview

PublisherHmbown
RepositoryWizards-of-the-Ghosts
Skill namemass-suggestion
Stars
106
Forks
10
Bundled files
Instructions only
LicenseCC0-1.0
Links
Skill sourceRepository
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Mass Suggestion 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/Hmbown/Wizards-of-the-Ghosts.git /tmp/Wizards-of-the-Ghosts
mkdir -p .claude/skills
cp -r /tmp/Wizards-of-the-Ghosts/generated/hermes/influence-and-behavior/mass-suggestion .claude/skills/mass-suggestion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mass Suggestion 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 Mass Suggestion 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 Mass Suggestion 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.

Mass Suggestion

Craft a message that nudges an entire audience toward a single action.

What This Skill Does

Mass Suggestion plants the same idea in many minds simultaneously. The real-world version is broadcast persuasion: campaign announcements, company-wide emails, product launch copy, or public statements designed to move a large group in a specific direction. The scale amplifies both impact and risk. In this grimoire, Mass Suggestion is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Mass Suggestion (spell).

When To Use

  • You need to draft a company announcement, campaign message, or broadcast communication that drives a specific collective action.
  • The audience is large enough that individual persuasion is impractical — you need one message that works at scale.

Prerequisites

  • No extra runtime dependencies beyond Hermes Agent and the normal toolset for this session.

Procedure

  1. Restate the target, the success condition, and any no-touch boundaries before taking action.
  2. Define the single action you want the audience to take.
  3. Identify the audience segments and what motivates each one.
  4. Draft the message to work for the broadest segment while not alienating others.
  5. Apply the manipulation audit at amplified scrutiny: at scale, even mild dark patterns cause real harm.
  6. Return the message with deployment guidance and a note on which audience segments it may not reach.
  7. Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.

Deliverables

  • The broadcast message, optimized for the target audience and action.
  • Segment analysis: which groups will respond and which will not.
  • An amplified manipulation audit: risks that emerge specifically because of scale.

Pitfalls / Guardrails

  • Keep the metaphor anchored to a real mechanism instead of drifting into lore.
  • Scaled influence requires scaled scrutiny. A nudge that is harmless one-on-one can become coercive when broadcast to thousands.
  • Refuse propaganda patterns: emotional manipulation without factual basis, manufactured consensus, or suppression of dissent.

Verification

  • Check that the result includes every deliverable promised above.
  • Check that confirmed facts, assumptions, and inferences are visibly separated.
  • Check that the metaphor still maps cleanly to a real operational mechanism.

Example Invocation

text
/mass-suggestion draft a broadcast message that moves this audience toward this action, with extra scrutiny for scale-amplified manipulation

Frequently asked questions

What does the Mass Suggestion AI skill do?

Mass Suggestion plants the same idea in many minds simultaneously. The real-world version is broadcast persuasion: campaign announcements, company-wide emails, product launch copy, or public statements designed to move a large group in a specific direction. The scale amplifies both impact and risk.

Why use Mass Suggestion on TypingMind?

Because you install it once and use it with any model. Mass Suggestion 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 Mass Suggestion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Hmbown/Wizards-of-the-Ghosts/tree/main/generated/hermes/influence-and-behavior/mass-suggestion. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Mass Suggestion?

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 Mass Suggestion?

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

Is the Mass Suggestion AI skill free?

Yes. It is published on GitHub by Hmbown under the CC0-1.0 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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