Stinking Cloud

Community

Hmbown

stinking-cloud

In D&D, Stinking Cloud fills an area with nauseating gas — creatures inside are incapacitated but the terrain itself is undamaged. The real-world version is area denial: making a zone, endpoint, or resource unusable to unwanted traffic without permanently destroying or modifying it. Rate limiting, IP-range blocks, honeypots, tarpits, geographic restrictions. Stinking Cloud is defensive — it protects a perimeter by making the area inside it miserable for intruders while leaving the underlying infrastructure intact.

Overview

Publisher	Hmbown
Repository	`Wizards-of-the-Ghosts`
Skill name	`stinking-cloud`
Stars	106
Forks	10
Bundled files	Instructions only
License	CC0-1.0
Links	Skill source Repository

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 Stinking Cloud AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Hmbown/Wizards-of-the-Ghosts/tree/main/generated/hermes/containment-and-intervention/stinking-cloud

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/containment-and-intervention/stinking-cloud .claude/skills/stinking-cloud

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Stinking Cloud 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 Stinking Cloud 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 Stinking Cloud 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.

Stinking Cloud

Make an area inhospitable without destroying it.

What This Skill Does

When To Use

You need to deter access to a resource, endpoint, or zone without destroying it.
Defensive measures should slow, frustrate, or redirect unwanted traffic rather than block it outright.
You want to set up a honeypot, tarpit, or deterrent zone that wastes attackers' time and resources.

Prerequisites

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

Procedure

Restate the target, the success condition, and any no-touch boundaries before taking action.
Define the area to deny: which endpoints, IP ranges, geographic zones, or resources.
Choose the deterrent mechanism: rate limiting, tarpitting, CAPTCHA walls, honeypots, or access throttling.
Deploy the deterrent and verify it affects only the intended zone.
Monitor for legitimate traffic caught in the cloud and create bypass mechanisms if needed.
Set review criteria for when the cloud should be lifted or the perimeter adjusted.
Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.

Deliverables

A deployed area-denial mechanism with clear boundaries.
Monitoring for false positives: legitimate users caught in the deterrent zone.
A review schedule for adjusting or lifting the deterrent.

Pitfalls / Guardrails

Keep the metaphor anchored to a real mechanism instead of drifting into lore.
Area denial must not trap legitimate users without recourse. Always provide a way for real users to verify themselves and pass through.
Stinking Cloud is temporary and defensive. If you need permanent access control, use proper authentication and authorization.
Honeypots and tarpits must be clearly separated from production systems to avoid contamination.

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
/stinking-cloud set up area-denial defenses — rate limits, tarpits, honeypots, or deterrent zones that make an area inhospitable to unwanted traffic without destroying the underlying infrastructure

Frequently asked questions

What does the Stinking Cloud AI skill do?

Why use Stinking Cloud on TypingMind?

Because you install it once and use it with any model. Stinking Cloud 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 Stinking Cloud in TypingMind?

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

Which AI models can use Stinking Cloud?

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 Stinking Cloud?

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

Is the Stinking Cloud 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.

View all

Caveman Compress

JuliusBrussee

CommunityPopular

Compress a memory file such as CLAUDE.md or a todo list into caveman format to save input tokens, keeping a readable backup. Trigger: /caveman-compress.

Caveman Discover

Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.

Caveman Manage

Inspect Caveman Cloud's experiment lifecycle and block unsafe execution. Use when asked to start, approve, cancel, promote or roll back a Caveman experiment.

Caveman Setup

Wire a repository through the Caveman Cloud gateway so every LLM request is measured, with no behavior change. Use for "set up caveman" or adding LLM spend observability.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Stinking Cloud

What This Skill Does

When To Use

Prerequisites

Procedure

Deliverables

Pitfalls / Guardrails

Verification

Example Invocation

Frequently asked questions

Related AI Skills

Set up your own AI workspace now