Clinical Trials Database
google-deepmind/science-skills
Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.
Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training…
Install Totalsegmentator
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentator --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .claude/skills/totalsegmentator && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .claude/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentatorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentator --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .agents/skills/totalsegmentator && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .agents/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentator --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .cursor/skills/totalsegmentator && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .cursor/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/totalsegmentator--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentator --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .gemini/skills/totalsegmentator && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .gemini/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentatorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .github/skills/totalsegmentator && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .github/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill totalsegmentator --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/totalsegmentator .opencode/skills/totalsegmentator && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "totalsegmentator" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/totalsegmentator into .opencode/skills/totalsegmentator/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "totalsegmentator", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
totalsegmentator- GitHub stars
- 330
- Token cost
- ~1.4k tokens
- SKILL.md length
- 505 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 159
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training…
- Works in 5 steps: Discover capabilities first when task or… → Build segmentation commands through… → Parse run_report.json, statistics.json,… → …
- Tasks that involve Clinical and healthcare research
- SKILL.md covers Quick Start, Route by User Intent, Safe Install and Smoke Check and Common Workflows, plus 2 more sections
- Runs Python scripts from its folder; calls pip and python
What it does
Totalsegmentator is an agent skill from VectorSpaceLab/AREX-Skill. Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training boundaries.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/repo-provenance.md`, `references/repo-routing-metadata.json` and `references/task-selection.md`).
It sits in Research & Science, covering Clinical and healthcare research. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Clinical and healthcare research
Example prompts
- “/totalsegmentator”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Discover capabilities first when task or class names are uncertain: totalseg_info --json or capability-discovery.
- Build segmentation commands through segmentation-workflows; add --report for automation.
- Parse run_report.json, statistics.json, multilabel outputs, probabilities, and combined masks through outputs-and-statistics.
- Use runtime-configuration for install/import checks, CPU/GPU/MPS decisions, model weights, offline setup, licenses, and usage-stat settings.
- Use dicom-and-formats before long runs when inputs are DICOM folders/zips, DICOM output is requested, or crop-to-body preprocessing is…
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pippython
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Totalsegmentator loads about 1.4k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 55 tokens; SKILL.md has 505 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 505 words, ~1,359 tokens.
Download SKILL.mdSave it as
.claude/skills/totalsegmentator/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- totalsegmentator
- description
- Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training boundaries.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- Apache 2.0
TotalSegmentator
Use this skill when a user asks about TotalSegmentator, the TotalSegmentator CLI, the totalsegmentator Python package, anatomical CT/MR segmentation tasks, model-weight or license setup, segmentation output parsing, DICOM/NIfTI handling, or TotalSegmentator-style nnU-Net retraining.
TotalSegmentator outputs are research/workflow artifacts unless the surrounding product has its own approved clinical validation. Preserve input provenance, verify task/class choices, and prefer machine-readable JSON outputs over scraping stdout.
Quick Start
- Discover capabilities first when task or class names are uncertain:
totalseg_info --jsonor capability-discovery. - Build segmentation commands through segmentation-workflows; add
--report <path.json>for automation. - Parse
run_report.json,statistics.json, multilabel outputs, probabilities, and combined masks through outputs-and-statistics. - Use runtime-configuration for install/import checks, CPU/GPU/MPS decisions, model weights, offline setup, licenses, and usage-stat settings.
- Use dicom-and-formats before long runs when inputs are DICOM folders/zips, DICOM output is requested, or crop-to-body preprocessing is needed.
Route by User Intent
| User intent | Read this |
|---|---|
List tasks, classes, modalities, license flags, or valid --roi_subset names | capability-discovery |
| Build or run a CT/MR segmentation CLI/API workflow | segmentation-workflows |
| Validate reports, statistics, masks, multilabel headers, probabilities, or combined masks | outputs-and-statistics |
| Fix install/import/backend issues, choose devices, pre-stage weights, configure offline or licensed tasks | runtime-configuration |
| Validate NIfTI/DICOM inputs, DICOM SEG/RTSTRUCT outputs, modality detection, or crop-to-body preprocessing | dicom-and-formats |
| Use contrast phase, CT/MR modality, body stats, or Evans index helper CLIs | auxiliary-analysis |
| Plan retraining, dataset conversion, benchmark evaluation, or model-contribution work | advanced-training |
Safe Install and Smoke Check
Install the public package in the user's chosen environment:
pip install TotalSegmentatorThen run safe checks that do not download model weights:
totalseg_info --json
python scripts/check_install.py --task total --class-name liver --jsonThe root helper verifies package metadata, importability, registry access, selected task/class names, and console-script availability. It does not run segmentation, validate licenses against the network, or download weights.
Show full SKILL.md (227 more words)Show less
Common Workflows
- Automation pipeline: discover task/classes with
totalseg_info --json, build aTotalSegmentatorcommand with--reportand optional--statistics, then parse JSON files through the outputs sub-skill. - CPU-only run: choose
--device cpu, add--fastor a small--roi_subset, and use the segmentation troubleshooting reference for memory/runtime limits. - Offline deployment: use runtime configuration to set a writable TotalSegmentator home, pre-stage weights, save any required license, and run read-only diagnostics before inference.
- DICOM output: validate the input as DICOM first, install the needed optional DICOM output dependency, and avoid requesting DICOM output from NIfTI input.
- Advanced research: use the training sub-skill only for explicit retraining/evaluation/contribution requests; ordinary segmentation should stay in the segmentation workflow.
Runtime References
- Read references/task-selection.md for task, class, modality, and license selection patterns.
- Read references/troubleshooting.md for cross-cutting install, data, CLI/API, optional dependency, model-weight, and license failures.
- Read references/repo-provenance.md to decide whether this skill is aligned with the source version.
references/repo-routing-metadata.jsoncontains structured metadata for managed router import.
Boundaries
- Do not hard-code task/class lists from memory; use
totalseg_infoortotalsegmentator.registry. - Do not run heavyweight segmentation, model downloads, licensed tasks, or training by default when the user only needs planning or validation.
- Do not expose license numbers, local cache paths, or environment paths in shared reports.
- Do not treat skipped native examples or heavyweight tests as passing; record why they are skipped and use safe JSON/helper checks where possible.
© VectorSpaceLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references) in skills/repositories/repo-skills/totalsegmentator of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/repo-provenance.md
- references/repo-routing-metadata.json
- references/task-selection.md
- references/troubleshooting.md
- scripts/check_install.py
- sub-skills
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Totalsegmentator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Totalsegmentator this skillVectorSpaceLab/AREX-Skill | 330 | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Clinical Trials Databasegoogle-deepmind/science-skills | 3.2k | 2 repos | ~3.2k | Automated safety check: Pass | Apache-2.0 | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None | |
| Biomedical Analysis Dispatchxjtulyc/MedgeClaw | 617 | 1 repos | ~2k | Automated safety check: Pass | None | |
| Research Proposalluwill/research-skills | 858 | — | ~4.4k | Automated safety check: Notes | None | |
| Medical Imaging ReviewLeonChaoX/qinyan-academic-skills | 943 | 3 repos | ~1.1k | Automated safety check: Notes | MIT |
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Related
Categories
Questions about Totalsegmentator
What does Totalsegmentator do?
Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training…. Totalsegmentator is an agent skill from VectorSpaceLab/AREX-Skill. Use TotalSegmentator as an installed package for medical-image segmentation, task discovery, runtime configuration, output parsing, DICOM handling, auxiliary analysis, and advanced training boundaries.
When should I use Totalsegmentator?
Totalsegmentator fits situations like: tasks that involve Clinical and healthcare research.
How do I install Totalsegmentator in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/totalsegmentator in VectorSpaceLab/AREX-Skill) into .claude/skills/totalsegmentator in your project. Claude Code loads it when a task matches its description.
How do I install Totalsegmentator in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a codex`. Or copy the skill folder (skills/repositories/repo-skills/totalsegmentator in VectorSpaceLab/AREX-Skill) into .agents/skills/totalsegmentator in your project. Codex loads it when a task matches its description.
Can I use Totalsegmentator in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill totalsegmentator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/totalsegmentator, .gemini/skills/totalsegmentator, .github/skills/totalsegmentator and .opencode/skills/totalsegmentator in your project.
What does Totalsegmentator need to run?
Going by SKILL.md and its folder, Totalsegmentator needs Python for the scripts in its folder and the command-line tools its instructions call (pip and python). Our summary lists: Python 3.
Does Totalsegmentator access the network?
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Totalsegmentator safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Totalsegmentator use?
Totalsegmentator is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Totalsegmentator use?
About 1.4k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.9k tokens, read only when the agent opens those files.
What are the alternatives to Totalsegmentator?
Skills that share tags, products or a category with Totalsegmentator: Clinical Trials Database (google-deepmind/science-skills, 3.2k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars) and Research Proposal (luwill/research-skills, 858 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Totalsegmentator?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 330 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.