Agent skill

Radiology Data

by huang-sir1 in huang-sir1/radiology-skills

Plan/audit imaging provenance, DICOM de-identification, sharing, repositories and retention; not ethics approval.

Custom licenceAuto-check passedResearch & Science

Install Radiology Data

skills CLI
$ npx skills add huang-sir1/radiology-skills --skill radiology-data -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install huang-sir1/radiology-skills radiology-data --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/huang-sir1/radiology-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/radiology-skills/skills/radiology-data .claude/skills/radiology-data && rm -rf skills-src

Use ~/.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/

Facts

Skill name
radiology-data
GitHub stars
1.9k
Token cost
~2.2k tokens
SKILL.md length
846 words
Files
14 (incl. references)
Skills in repo
39
Repo updated
First seen
Licence
Custom licence

At a glance

Plan/audit imaging provenance, DICOM de-identification, sharing, repositories and retention; not ethics approval.

  • Works in 9 steps: Freeze the applicable policy passport… → Inventory result-supporting data:… → For lifecycle planning, open… → …
  • Tasks that involve Clinical and healthcare research
  • SKILL.md covers Core stance, When to use, When to open extra files and Workflow, plus 2 more sections
  • Runs Python scripts from its folder

What it does

Radiology Data is an agent skill from huang-sir1/radiology-skills. Plan/audit imaging provenance, DICOM de-identification, sharing, repositories and retention; not ethics approval.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including reference files (for example `README.md`, `agents/openai.yaml` and `references/ai-radiogenomics-public-resources.md`).

It sits in Research & Science, covering Clinical and healthcare research.

When your agent uses it

  • Tasks that involve Clinical and healthcare research

Example prompts

  • “/radiology-data”

Requirements

  • Python 3

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Freeze the applicable policy passport when a DMP/DMS, retention or access decision is in
  2. Inventory result-supporting data: imaging, radiomic feature tables, clinical data,
  3. For lifecycle planning, open data-lifecycle-management-plan.md; bind raw and derived
  4. For public-resource planning, open ai-radiogenomics-public-resources.md and mark each
  5. Classify each as public / depositable / restricted (privacy, consent, DUA, commercial).
  6. De-identify imaging (dicom-deidentification.md); freeze a closed object/payload/package
  7. Pick repositories (repositories.md): images → TCIA/Zenodo; features/code → Zenodo/
  8. Draft statements (availability-and-fair.md) with accessions/placeholders; write dataset
  9. Flag restrictions honestly: reason, controller, review route, conditions. For retention,

What it can do on your machine

Read from SKILL.md and the folder at commit aaa0fe6. 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 script files (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Radiology Data loads about 2.2k tokens when it runs, and up to ~16k if it reads all its reference files. Until then it costs about 32 tokens; SKILL.md has 846 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~16k

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); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 846 words (~2,208 tokens).

“Build or audit a living data-lifecycle/DMP record, prepare submission-ready Data Availability and Code/Model Availability statements, plan DICOM de-identification, choose repositories, and check FAIR — for imaging and imaging+omics studies.”

— opening of SKILL.md by huang-sir1, Custom licence
name
radiology-data

Read the full SKILL.md on GitHub

Files

SKILL.md and 13 other files (references) in radiology-skills/skills/radiology-data of huang-sir1/radiology-skills.

  • SKILL.md
  • README.md
  • agents/openai.yaml
  • references/ai-radiogenomics-public-resources.md
  • references/availability-and-fair.md
  • references/chinese-clinical-text-abstraction.md
  • references/cohort-assembly-and-id-reconciliation.md
  • references/data-dictionary-spec.md
  • references/data-lifecycle-management-plan.md
  • references/dicom-deidentification.md
  • references/outcome-and-followup-data.md
  • references/repositories.md
  • templates/data-lifecycle-plan.md
  • tests/test_dicom_deidentification_contracts.py

Open the folder on GitHubat commit aaa0fe6

Compare with similar skills

Radiology Data 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.

Radiology Data compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Radiology Data this skillhuang-sir1/radiology-skills1.9k—~2.2kAutomated safety check: PassCustom licence
Clinical Trials Databasegoogle-deepmind/science-skills3.2k2 repos~3.2kAutomated safety check: PassApache-2.0
CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw6171 repos~1.8kAutomated safety check: PassNone
Biomedical Analysis Dispatchxjtulyc/MedgeClaw6171 repos~2kAutomated safety check: PassNone
Research Paperluwill/research-skills862—~1.9kAutomated safety check: PassNone
Research Proposalluwill/research-skills862—~4.5kAutomated safety check: NotesNone

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  • Radiology Consensus Guideline

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Questions about Radiology Data

What does Radiology Data do?

Plan/audit imaging provenance, DICOM de-identification, sharing, repositories and retention; not ethics approval. Radiology Data is an agent skill from huang-sir1/radiology-skills. Plan/audit imaging provenance, DICOM de-identification, sharing, repositories and retention; not ethics approval.

When should I use Radiology Data?

Radiology Data fits situations like: tasks that involve Clinical and healthcare research.

How do I install Radiology Data in Claude Code?

Run `npx skills add huang-sir1/radiology-skills --skill radiology-data -a claude-code`. Or copy the skill folder (radiology-skills/skills/radiology-data in huang-sir1/radiology-skills) into .claude/skills/radiology-data in your project. Claude Code loads it when a task matches its description.

How do I install Radiology Data in Codex?

Run `npx skills add huang-sir1/radiology-skills --skill radiology-data -a codex`. Or copy the skill folder (radiology-skills/skills/radiology-data in huang-sir1/radiology-skills) into .agents/skills/radiology-data in your project. Codex loads it when a task matches its description.

Can I use Radiology Data 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 huang-sir1/radiology-skills --skill radiology-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/radiology-data, .gemini/skills/radiology-data, .github/skills/radiology-data and .opencode/skills/radiology-data in your project.

What does Radiology Data need to run?

Going by SKILL.md and its folder, Radiology Data needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Radiology Data access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Radiology Data 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. Review the folder before installing.

What licence does Radiology Data use?

Radiology Data has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Radiology Data use?

About 2.2k tokens (SKILL.md is roughly 8.8k 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 13k tokens, read only when the agent opens those files.

What are the alternatives to Radiology Data?

Skills that share tags, products or a category with Radiology Data: 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 Paper (luwill/research-skills, 862 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Radiology Data?

huang-sir1 (a GitHub user) maintains it in huang-sir1/radiology-skills, which has 1,923 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on September 21, 2026.

Source: huang-sir1/radiology-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.