# Slicer: a skill for code and 3D scenes Editorial description and links. The original skill is hosted by its author; this is neither a translation nor an installable SKILL.md. Find answers in 3D Slicer source and documentation, prepare a script and, with a separately connected MCP server, inspect a real scene using a public sample. ## Before you start — editorial notes Our editorial guide to Steve Pieper’s skill. MCP is a separate setup step; this release was source-reviewed. 1. Read the pinned SKILL.md and setup.sh. Keep the complete repository at that revision in a separate reference folder. 2. Register the skill using your agent’s supported mechanism. Start with web mode and no indexes; full mode involves substantial downloads. 3. For scene control, install 3D Slicer separately, review slicer-mcp-server.py and configure local MCP. It executes Python with Slicer privileges; use an isolated environment. 4. Check the connection and start with public CTChest data. Preserve actual scene information and screenshots; connection failures are not inspection results. Step-by-step article: https://kossolapov.com/en/blog/ct-ai-slicer-ctchat-merlin Editorial selection based on source review and use cases. Comparative superiority has not been tested. Author: Steve Pieper — https://github.com/pieper Original skill: Steve Pieper and contributors. Editorial guide: kossolapov.com. Original: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/SKILL.md Revision: c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f License: Apache-2.0 — https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/LICENSE ## Use cases - Find APIs for a Slicer Python script or extension - Understand MRML scenes and view controls - Prepare a CTChest demonstration through the separate MCP server ## Outcome Code and documentation references and a verifiable action plan; with MCP available, actual scene information and a screenshot. ## Example task Prepare Slicer using the pinned skill: first check the environment and choose web mode without indexes. Use only the public CTChest sample for a demonstration and report an unavailable MCP connection explicitly. ## Requirements and limitations agents: - An agent that can read Agent Skills instructions; MCP support is separately required for live Slicer control tools: - Git, Bash and Perl for the setup helper; web mode avoids large source clones - Installed 3D Slicer and its Python console for the separate slicer-mcp-server.py - Optional Python search dependencies and disk space for BM25/hybrid indexes paidDependencies: - The chosen AI host or remote compute may incur costs limitations: - Source-reviewed only: neither this skill nor its MCP server was run for this release. - The MCP bridge can execute Python with the privileges of the Slicer process; use an isolated public-sample environment. - MCP responses can reach a cloud AI host; a local Slicer window does not guarantee local-only data handling. - Installing the skill does not install Slicer or connect MCP. The full setup can clone many repositories; choose its mode deliberately. - Software control and screenshots are not clinical interpretation or a complete CT review. - The pinned SKILL.md links to references/mcp.md, which is absent in that revision. Inspect the included slicer-mcp-server.py and verify MCP setup separately; the referenced setup guide is unavailable. ## Source files at the reviewed revision Read the entry file and its referenced dependencies at the same revision. - LICENSE: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/LICENSE SHA-256: 098a837115eee56c633f88d0fa6dd197321296e1228873f4b402e49fe4bd7de0; bytes: 11358 - README.md: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/README.md SHA-256: f30f73c80c253f5b32aa8b08e9a9d59d494ee64a87e2b9ee4361fa8c3a47d7e5; bytes: 6664 - SKILL.md: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/SKILL.md SHA-256: 7d89e36438fcc064a2cc9fe9acdf3fd51b446ff22a78628b707c357b76b5b4bd; bytes: 48796 - slicer-mcp-server.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/slicer-mcp-server.py SHA-256: 31b0cff2880a248f173964a8d8edb591d3eadcc4c019889e8f32eadb65f6abbc; bytes: 20282 - setup.sh: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/setup.sh SHA-256: 280bb8e98ccd55327daa00f8600169d06496205ca8c1904c5ef97c7aae16e12b; bytes: 31663 - .gitignore: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/.gitignore SHA-256: 61a090f79c20c43aa16fd4777d3d8d650a5f8cc130ae0ca2fa2cc94ab623b0cf; bytes: 773 - scripts/bm25_lib.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/bm25_lib.py SHA-256: 823f2c6bb723de69af8d10ed58ed75b781fb62221907b4b0154a694abb0031ac; bytes: 5246 - scripts/build_bm25.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/build_bm25.py SHA-256: 426f27f1bdd978c79c781e46a92e51ffde2be3b2a064d111c060ab8094bc1b28; bytes: 7928 - scripts/build_vector.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/build_vector.py SHA-256: a521b4d3f8b534b7e6bd0ac3456532fb73432a3fa60b0392a3e52311823f4265; bytes: 5302 - scripts/extract_pw_stats.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/extract_pw_stats.py SHA-256: 278b9f7a2c739e1793326b8d14ce58060adedf6c163481d4c96c79526d558cde; bytes: 13645 - scripts/requirements.txt: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/requirements.txt SHA-256: 7fb69c0918a70a145f4ff7b0174745877c6c6f7f97b70aafe40b22767e56459e; bytes: 35 - scripts/vector_lib.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/scripts/vector_lib.py SHA-256: 0f91e05526506213c831d6a88af47407175f68714f443783347f1fd333820031; bytes: 8688 - slicer-skill-search-mcp.py: https://github.com/pieper/slicer-skill/blob/c3b9f3bbc2b95938e73f1ad0c2e6c01a8fd2e32f/slicer-skill-search-mcp.py SHA-256: 2e80028edb1a1f5b02b556cd653df7ea659b71db66cc4509a70cff5c62b8e765; bytes: 12575 ## The complete kit in one ZIP CT toolkit: one ZIP for Codex and Claude Code: https://kossolapov.com/en/materials/ct-ai-kit ZIP: https://kossolapov.com/downloads/ct-ai-kit/CT-AI-Kit.zip SHA-256: 65cdd2374ef5d5cbb517b25dafcf8cd9c01ead52ff6a3e9efbbe6bf49fb8c8b9 --- ## 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