Clinical Trials Database
google-deepmind/science-skills
Query ClinicalTrials.gov via APIv2. An agent skill from google-deepmind/science-skills.
De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support.
Install Dicom Anonymizer
$ npx skills add aipoch/medical-research-skills --skill dicom-anonymizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aipoch/medical-research-skills dicom-anonymizer --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/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .claude/skills/dicom-anonymizer && 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 "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .claude/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizerType 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 aipoch/medical-research-skills --skill dicom-anonymizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aipoch/medical-research-skills dicom-anonymizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .agents/skills/dicom-anonymizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .agents/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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 aipoch/medical-research-skills --skill dicom-anonymizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aipoch/medical-research-skills dicom-anonymizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .cursor/skills/dicom-anonymizer && 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 "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .cursor/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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/aipoch/medical-research-skills.git --path scientific-skills/Other/dicom-anonymizer--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 aipoch/medical-research-skills --skill dicom-anonymizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aipoch/medical-research-skills dicom-anonymizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .gemini/skills/dicom-anonymizer && 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 "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .gemini/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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 aipoch/medical-research-skills dicom-anonymizerInstalls 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 aipoch/medical-research-skills --skill dicom-anonymizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .github/skills/dicom-anonymizer && 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 "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .github/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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 aipoch/medical-research-skills --skill dicom-anonymizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aipoch/medical-research-skills dicom-anonymizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/scientific-skills/Other/dicom-anonymizer .opencode/skills/dicom-anonymizer && 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 "dicom-anonymizer" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Other/dicom-anonymizer into .opencode/skills/dicom-anonymizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dicom-anonymizer", 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
dicom-anonymizer- GitHub stars
- 2k
- Token cost
- ~1.4k tokens
- SKILL.md length
- 618 words
- Files
- 9 (incl. scripts, references)
- Skills in repo
- 578
- Repo updated
- First seen
- Licence
- MIT
At a glance
De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support.
- Works in 5 steps: Confirm the input type, output target,… → Check whether the request is asking for… → Use the packaged script for supported… → …
- Tasks that involve Clinical and healthcare research
- SKILL.md covers Quick Check, Audit-Ready Commands, When to Use and Workflow, plus 11 more sections
- Runs Python scripts from its folder; calls python
What it does
Dicom Anonymizer is an agent skill from aipoch/medical-research-skills. De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `POLISH_CHANGELOG.md`, `dicom-anonymizer_audit_result_v2.json` and `references/audit-reference.md`).
It sits in Research & Science, covering Clinical and healthcare research. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.
When your agent uses it
- Tasks that involve Clinical and healthcare research
Example prompts
- “/dicom-anonymizer”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Confirm the input type, output target, batch needs, and whether study linkage must be preserved.
- Check whether the request is asking for script execution, audit-log planning, or a manual anonymization checklist.
- Use the packaged script for supported local workflows; if dependencies or files are missing, provide a bounded fallback rather than…
- Return the anonymization plan or result with assumptions, preserved identifiers, and remaining manual QA requirements.
- If the request exceeds supported scope, stop and state the specific boundary.
What it can do on your machine
Read from SKILL.md and the folder at commit 686e09d. 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 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
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
Dicom Anonymizer loads about 1.4k tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 38 tokens; SKILL.md has 618 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 aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 618 words, ~1,423 tokens.
Download SKILL.mdSave it as
.claude/skills/dicom-anonymizer/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- dicom-anonymizer
- description
- De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support.
- license
- MIT
- author
- AIPOCH
DICOM Anonymizer
Structured DICOM de-identification support for research preparation workflows.
Quick Check
python -m py_compile scripts/main.pyAudit-Ready Commands
python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/smoke_test.pyWhen to Use
- Prepare imaging data for research sharing
- Batch-anonymize DICOM folders while preserving study linkage
- Review whether a workflow still needs manual PHI QA
- Generate audit logs for compliance documentation
Workflow
- Confirm the input type, output target, batch needs, and whether study linkage must be preserved.
- Check whether the request is asking for script execution, audit-log planning, or a manual anonymization checklist.
- Use the packaged script for supported local workflows; if dependencies or files are missing, provide a bounded fallback rather than claiming successful anonymization.
- Return the anonymization plan or result with assumptions, preserved identifiers, and remaining manual QA requirements.
- If the request exceeds supported scope, stop and state the specific boundary.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
--input, -i | string | Yes | - | Input DICOM file or directory |
--output, -o | string | Yes | - | Output DICOM file or directory |
--batch, -b | flag | No | false | Enable directory processing |
--preserve-studies | flag | No | false | Preserve study linkage with pseudonyms |
--keep-tags | string | No | - | Comma-separated tags to preserve |
--remove-private | flag | No | true | Remove private tags |
--audit-log, -a | string | No | - | Optional JSON audit log path |
--overwrite | flag | No | false | Allow overwriting output files |
Usage
# Single file
python scripts/main.py --input scan.dcm --output anonymized.dcm
# Batch directory
python scripts/main.py --input ./dicoms/ --output ./anon/ --batch --preserve-studies
# With audit log
python scripts/main.py --input scan.dcm --output anon.dcm --audit-log audit.json
# Keep specific tags
python scripts/main.py --input scan.dcm --output anon.dcm --keep-tags "PatientAge,StudyDate"Returns
- Anonymized DICOM artifact or bounded execution plan
- Summary of preserved and anonymized identifiers
- Explicit reminder of remaining QA steps before external release
Scope Boundaries
- Supports DICOM de-identification workflows, not legal certification
- Does not remove burned-in image annotations from pixel data
- Does not replace institutional privacy review or release approval
- De-anonymization is not supported: SHA-256 hashing used for PHI values is a one-way operation by design. Original patient data cannot be recovered from anonymized files. If you need to trace back to original data, consult your institutional data governance office before anonymizing.
De-anonymization Requests
If asked to recover original patient data or reverse anonymization, respond:
"Anonymization performed by this tool is irreversible by design. PHI values are replaced using one-way SHA-256 hashing — the original data is not retained by this tool and cannot be recovered. If you need access to the original patient data, contact your institutional data governance or privacy office."
Show full SKILL.md (259 more words)Show less
Stress-Case Rules
For complex requests, always include these blocks:
- Assumptions
- Hard Constraints
- Anonymization Path
- Residual PHI Risks
- Manual QA Before Release
Input Validation
This skill accepts requests involving DICOM anonymization, PHI-tag removal, research export preparation, or audit-log planning for medical images.
If the user's request does not involve DICOM de-identification — for example, asking to diagnose from images, convert image formats unrelated to PHI removal, or certify HIPAA compliance — do not proceed with the workflow. Instead respond:
"dicom-anonymizer is designed to support DICOM de-identification workflows for research preparation. Your request appears to be outside this scope. Please provide a DICOM input path and output target, or use a more appropriate tool for your task."
References
- references/phi_tags.json — PHI-related DICOM tags used by the packaged workflow
- references/audit-reference.md — Supported scope, audit commands, and fallback boundaries
Output Requirements
Every final response must include:
- Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks
Error Handling
- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If
scripts/main.pyfails, report the failure point, summarize what still can be completed safely, and provide a manual fallback. - Do not fabricate files, citations, data, search results, or execution outcomes.
Response Template
- Objective
- Inputs Received
- Assumptions
- Workflow
- Deliverable
- Risks and Limits
- Next Checks
© aipoch, MIT. 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 8 other files (scripts, references) in scientific-skills/Other/dicom-anonymizer of aipoch/medical-research-skills.
- SKILL.md
- POLISH_CHANGELOG.md
- dicom-anonymizer_audit_result_v2.json
- references/audit-reference.md
- references/phi_tags.json
- references/requirements.txt
- requirements.txt
- scripts/main.py
- scripts/smoke_test.py
Open the folder on GitHubat commit 686e09d
Compare with similar skills
Dicom Anonymizer 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 |
|---|---|---|---|---|---|---|
| Dicom Anonymizer this skillaipoch/medical-research-skills | 2k | — | ~1.4k | Automated safety check: Pass | MIT | |
| 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 Dicom Anonymizer
What does Dicom Anonymizer do?
De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support. Dicom Anonymizer is an agent skill from aipoch/medical-research-skills. De-identify DICOM medical images by removing PHI tags for research sharing, with audit logging and study-linkage preservation support.
When should I use Dicom Anonymizer?
Dicom Anonymizer fits situations like: tasks that involve Clinical and healthcare research.
How do I install Dicom Anonymizer in Claude Code?
Run `npx skills add aipoch/medical-research-skills --skill dicom-anonymizer -a claude-code`. Or copy the skill folder (scientific-skills/Other/dicom-anonymizer in aipoch/medical-research-skills) into .claude/skills/dicom-anonymizer in your project. Claude Code loads it when a task matches its description.
How do I install Dicom Anonymizer in Codex?
Run `npx skills add aipoch/medical-research-skills --skill dicom-anonymizer -a codex`. Or copy the skill folder (scientific-skills/Other/dicom-anonymizer in aipoch/medical-research-skills) into .agents/skills/dicom-anonymizer in your project. Codex loads it when a task matches its description.
Can I use Dicom Anonymizer 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 aipoch/medical-research-skills --skill dicom-anonymizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dicom-anonymizer, .gemini/skills/dicom-anonymizer, .github/skills/dicom-anonymizer and .opencode/skills/dicom-anonymizer in your project.
What does Dicom Anonymizer need to run?
Going by SKILL.md and its folder, Dicom Anonymizer needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Dicom Anonymizer 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 Dicom Anonymizer 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 Dicom Anonymizer use?
Dicom Anonymizer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Dicom Anonymizer use?
About 1.4k tokens (SKILL.md is roughly 5.7k 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 572 tokens, read only when the agent opens those files.
What are the alternatives to Dicom Anonymizer?
Skills that share tags, products or a category with Dicom Anonymizer: 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 Dicom Anonymizer?
aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,978 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.
Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.