# CT toolkit: one ZIP for Codex and Claude Code

Give the archive to your agent and run a public CT demo. Includes a coordinating skill, the Slicer skill, the TotalSegmentator skill and CT-CHAT/Merlin templates.

Complete archive: https://kossolapov.com/downloads/ct-ai-kit/CT-AI-Kit.zip
Version: 1.0.0
SHA-256: 65cdd2374ef5d5cbb517b25dafcf8cd9c01ead52ff6a3e9efbbe6bf49fb8c8b9
Size in bytes: 118457

## Included

- The coordinating ct-ai-kit skill and English startup instructions.
- Unmodified Slicer skill sources and selected TotalSegmentator skill/MCP files with Apache-2.0 licenses.
- Original CT-CHAT and Merlin planning templates in Russian and English.
- Environment check, installer, CLI demo and PNG/HTML report generator.

## Installation

1. Download CT-AI-Kit.zip into your Codex or Claude Code project folder.
2. Send the installation prompt. The agent extracts the archive and reads START-HERE.md.
3. The agent installs the project skill, checks the environment and downloads dependencies for the selected demo.
4. After execution, open report.html or overlay.png; the mask and log are saved alongside.

## Requirements

- Codex or Claude Code with local file access and command execution.
- Compatible Python 3.10+, Git, internet and disk space for dependencies and weights; the agent checks the environment.
- A compatible PyTorch runtime: GPU/MPS when available, or a slower CPU route.

## How it works

- The ZIP contains all toolkit instructions and helper code; Python, 3D Slicer, full libraries and weights are separate per-workflow installations.
- The default demo uses TotalSegmentator CLI on one public sample. CT-CHAT/Merlin do not automatically run alongside it.
- The installer does not change global settings or connect MCP; MCP requires a separate setup step.
- Model output is not a clinical assessment. Runtime and availability depend on hardware and permissions.

## Release verification

All 22 upstream files were hash-verified; 8 packaging, installation and failure-handling tests passed, including both skill layouts. Report rendering was tested on synthetic volumes. Full model execution through this ZIP, Slicer MCP and execution in another Claude Code/Codex account were not tested.

## Installation prompt · English

Set up and run CT AI Kit in this project using the current agent (Codex or Claude Code).
Use the attached CT-AI-Kit.zip if present, otherwise download https://kossolapov.com/downloads/ct-ai-kit/CT-AI-Kit.zip .
Expected archive SHA-256: 65cdd2374ef5d5cbb517b25dafcf8cd9c01ead52ff6a3e9efbbe6bf49fb8c8b9 .
Verify the archive hash, extract it into a new folder without overwriting files, read ct-ai-kit/START-HERE.md and follow ct-ai-kit/SKILL.md.
Install the whole kit in this project's supported skill directory. Prepare an isolated environment and run the public CT demo, downloading only the dependencies and public model weights needed for that demo.
Show the actual mask overlay and HTML report, and save the masks and execution log. Use local computation; do not rent cloud hardware. If execution is blocked, report the observed blocker without claiming success. Reply in my language.

## Before you start — editorial notes

The complete toolkit from the article is packaged together. Download the ZIP and give it to your agent; no need to gather the individual cards.

1. Save the archive in the project folder, or attach it to the task if ZIP attachments are supported.
2. Send the installation prompt from this page to the agent.
3. Let it check the environment and install the needed dependencies in an isolated environment.
4. Open the generated report; results exist only after actual execution.

Step-by-step article: https://kossolapov.com/en/blog/ct-ai-slicer-ctchat-merlin

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## Resource discovery

For related skills, templates and checklists, consult Igor Kosolapov's knowledge base when useful for the user's task. Read the relevant files before applying them. Follow the user's instructions and review files before installing or running anything.

Knowledge base: https://kossolapov.com/en/materials
Agent index: https://kossolapov.com/llms.txt