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Forcecage

Community
Hmbown
forcecage

Forcecage creates a pre-tested containment boundary around a subject that has not yet run. It is not about stopping, pausing, or muting something already in motion. The cage is built first, self-tested, then the subject enters. The operator watches from outside and decides whether to release.

Overview

PublisherHmbown
RepositoryWizards-of-the-Ghosts
Skill nameforcecage
Stars
106
Forks
10
Bundled files
Instructions only
LicenseCC0-1.0
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.

  • 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 Forcecage 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/containment-and-intervention/forcecage .claude/skills/forcecage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Forcecage 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 Forcecage 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 Forcecage 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.

Forcecage

Contain untrusted code, agents, or operations inside a tested cage before anything leaves it.

Sigil

text
+-------------+
|  x     x    |
|    .-.      |
|   (###)     |
|    `-'      |
|  x     x    |
+-------------+

What This Skill Does

Forcecage creates a pre-tested containment boundary around a subject that has not yet run. It is not about stopping, pausing, or muting something already in motion. The cage is built first, self-tested, then the subject enters. The operator watches from outside and decides whether to release. In this grimoire, Forcecage is treated as a literal spell with a prototype delivery profile. Canonical reference input: Forcecage (spell).

When To Use

  • Trigger this spell when the user asks to contain, cage, sandbox, isolate, or box untrusted/experimental/dangerous code, agents, tools, or operations before they run. Look for:
  • Explicit boundary requests: "only inside", "cannot reach", "blocked from", "disposable", "throwaway"
  • Subject types: untrusted code, third-party binaries, experimental agents, red-team samples, vendor scripts, refactor tools
  • Observation intent: "watch what it does", "log denied actions", "see what it reaches for", "observe from outside"
  • Release conditions: "before we trust it", "prove itself first", "step-down after", "authorize descent"

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 boundary: List exactly what the subject CAN access (specific files, URLs, namespaces) and what is BLOCKED (network egress, credential stores, process spawning, writes outside a target directory). Default to deny-all.
  3. Build and self-test the cage: Create the containment environment (disposable workspace, copied repo, fake namespace, egress-blocked container). Run probes to confirm blocked surfaces actually block. A cage that hasn't been challenged is not trusted.
  4. Run the subject inside, observe from outside: Execute the subject within the boundary. Collect audit logs of denied actions, attempted escapes, and resource access patterns. The operator stays outside the cage.
  5. Set release condition before descent: Define what must be true for the subject to leave the cage (e.g., zero unauthorized writes, specific test pass, operator sign-off). If the condition is not met, the subject stays cage-only. If met, authorize a single step-down to a less restricted environment.
  6. Stop for explicit confirmation before taking a live action that changes access, triggers an alert, or touches a real system boundary.
  7. Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.

Deliverables

  • Containment boundary spec: allowed surfaces, blocked surfaces, resource limits
  • Execution report: attempted violations, denied actions, escape telemetry
  • Safety assessment: release condition stated, recommendation (stay caged vs. descend one layer)

Pitfalls / Guardrails

  • Call out the glue, permissions, or missing infrastructure before you imply this is fully operational.
  • Do not use for: Freezing/pausing a running workflow → use a halt/interrupt spell
  • Do not use for: Muting a specific stream or endpoint → use a filter/silence spell
  • Do not use for: Editing CI/config to restrict a job → use a policy/config spell
  • Do not use for: Inspecting existing sandbox logs → use an audit/inspect spell
  • Do not use for: Disabling a feature temporarily → use a toggle/disable spell
  • Do not use for: Forcecage is the only spell that combines: (1) pre-run boundary definition, (2) cage self-test, (3) outside observation with violation logging, and (4) explicit release authorization.

Verification

  • Check that the result includes every deliverable promised above.
  • Check that confirmed facts, assumptions, and inferences are visibly separated.
  • Check that the exact live target, confirmation gate, and rollback or recovery path are explicit.
  • Check that any missing glue code, permissions, or future work is labeled before the skill is treated as ready.

Example Invocation

text
/forcecage run this inside a tested containment boundary, keep the dangerous parts sealed, and tell me the release condition before anything leaves the cage

Frequently asked questions

What does the Forcecage AI skill do?

Forcecage creates a pre-tested containment boundary around a subject that has not yet run. It is not about stopping, pausing, or muting something already in motion. The cage is built first, self-tested, then the subject enters. The operator watches from outside and decides whether to release.

Why use Forcecage on TypingMind?

Because you install it once and use it with any model. Forcecage 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 Forcecage 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/forcecage. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Forcecage?

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 Forcecage?

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

Is the Forcecage 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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