Dicom Series Preflight

OrganizationPopular

NVIDIA

dicom-series-preflight

Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.

Overview

Publisher	NVIDIA
Repository	`skills`
Skill name	`dicom-series-preflight`
Stars	3.3K
Forks	397
Bundled files	8
License	Apache-2.0
Links	Skill source Repository Homepage

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.
8 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by NVIDIA on GitHub. Read the source before you install it.

Installation

Install the Dicom Series Preflight 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.

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/NVIDIA/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/dicom-series-preflight .claude/skills/dicom-series-preflight

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

Use it in TypingMind

Enable Dicom Series Preflight 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 Dicom Series Preflight 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 Dicom Series Preflight 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.

DICOM Series Preflight

Purpose

Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.
Use the wrapper exactly as documented; do not replace the upstream entrypoint with a handwritten implementation.
Manifest I/O: inputs are dicom_dir; outputs are preflight_json.

Instructions

Read skill_manifest.yaml before changing arguments, side effects, or validation gates.
Run scripts/preflight_series.py through the documented command below; keep outputs under a caller-provided run directory.
If a host agent exposes run_script, use run_script("scripts/preflight_series.py", args=[...]); otherwise run the Bash/Python command shown below.
Check the emitted JSON and paired verifier guidance before treating the run as evidence.

Available Scripts

Script	Purpose	Arguments
`scripts/preflight_series.py`	Primary entrypoint declared by skill_manifest.yaml.	`PATH_TO_DICOM_DIR`

Prerequisites

Runtime requirements: Python packages listed in runtime.side_effects.pip_packages.
NiBabel 5.4 or newer is required so extreme-oblique axes remain labeled consistently across reorientation.
Run commands from the repository root unless an existing section below says otherwise.

Limitations

Header-only; does not decode pixel data or detect burnt-in PHI.
Canonical orientation gate assumes LPS-derived CT axcodes L,P,S.
Compressed transfer syntax and multi-frame instances are warned, not decoded.
Single-directory scan; does not reconcile multiple studies in one tree.
Not for clinical deployment, regulatory de-identification, autonomous diagnosis, production ingestion without a vetted converter.

Troubleshooting

Error	Cause	Fix
Missing dependency or import error	Runtime package drift from `skill_manifest.yaml`.	Install the packages declared in the manifest or use the documented setup command.
Empty or schema-invalid output	Wrong input path, unsupported modality, or upstream failure.	Re-run with a known fixture and inspect the wrapper JSON plus stderr.
Validation gate failure	Output violated a declared engineering invariant.	Keep the failed evidence pack and use the gate message to repair inputs or wrapper code.

Scans a DICOM directory (one series per folder) without decoding pixels. Emits JSON with inventory, orientation axcodes, PHI flags, findings, and a preflight.verdict of pass, warn, or fail.

bash
python scripts/preflight_series.py PATH_TO_DICOM_DIR

Pair with verifiers/dicom_preflight_quality_v1 for a trusted preflight pack:

bash
make run-trusted SKILL=dicom_series_preflight \
  FIXTURE=skills/dicom-series-preflight/fixtures/clean_no_phi \
  OUT=runs/dicom_preflight_demo

Flagship workflow:

bash
make run-workflow \
  WORKFLOW=examples/workflows/dicom_preflight_gate.yaml \
  WORKFLOW_INPUT=skills/dicom-series-preflight/fixtures/clean_no_phi \
  WORKFLOW_OUT=runs/dicom_preflight_gate

Not for de-identification, private-tag review, or clinical clearance.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dicom Series Preflight AI skill do?

Used for header-only preflight of one DICOM series folder before conversion or inference. Not for de-identification or clinical clearance.

Why use Dicom Series Preflight on TypingMind?

Because you install it once and use it with any model. Dicom Series Preflight 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 Dicom Series Preflight in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NVIDIA/skills/tree/main/skills/dicom-series-preflight. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dicom Series Preflight?

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 Dicom Series Preflight?

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

Is the Dicom Series Preflight AI skill free?

Yes. It is published on GitHub by NVIDIA under the Apache-2.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

DICOM Series Preflight

Purpose

Instructions

Available Scripts

Prerequisites

Limitations

Troubleshooting

Bundled files

Frequently asked questions

Related AI Skills

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