Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add foryourhealth111-pixel/Vibe-Skills --skill pydicomgit clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/pydicom)<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/pydicom"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/pydicom/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/pydicom"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/pydicom.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00110 | $0.03370 |
| Opus 5 | $0.00055 | $0.01685 |
| Sonnet 5 | $0.00022 | $0.00674 |
| Haiku 4.5 | $0.00011 | $0.00337 |
Grade A, and why
pydicom scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to pydicom — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pydicom
Overview
Pydicom is a pure Python package for working with DICOM files, the standard format for medical imaging data. This skill provides guidance on reading, writing, and manipulating DICOM files, including working with pixel data, metadata, and various compression formats.
Routing Boundary
Use this skill for DICOM files, tags, pixel data, anonymization, CT/MRI/PET/X-ray medical scans, PACS-oriented processing, and pydicom-specific coding. Generic PNG/JPEG image processing, OCR, screenshots, PubMed/literature search, ClinicalTrials.gov lookup, LaTeX/PDF builds, bioinformatics, chemistry, or generic Data Commons tasks are outside this skill.
When to Use This Skill
Use this skill when working with:
- Medical imaging files (CT, MRI, X-ray, ultrasound, PET, etc.)
- DICOM datasets requiring metadata extraction or modification
- Pixel data extraction and image processing from medical scans
- DICOM anonymization for research or data sharing
- Converting DICOM files to standard image formats
- Compressed DICOM data requiring decompression
- DICOM sequences and structured reports
- Multi-slice volume reconstruction
- PACS (Picture Archiving and Communication System) integration
Installation
Install pydicom and common dependencies:
uv pip install pydicom
uv pip install pillow # For image format conversion
uv pip install numpy # For pixel array manipulation
uv pip install matplotlib # For visualization
For handling compressed DICOM files, additional packages may be needed:
uv pip install pylibjpeg pylibjpeg-libjpeg pylibjpeg-openjpeg # JPEG compression
uv pip install python-gdcm # Alternative compression handler
Core Workflows
Reading DICOM Files
Read a DICOM file using pydicom.dcmread():
import pydicom
# Read a DICOM file
ds = pydicom.dcmread('path/to/file.dcm')
# Access metadata
print(f"Patient Name: {ds.PatientName}")
print(f"Study Date: {ds.StudyDate}")
print(f"Modality: {ds.Modality}")
# Display all elements
print(ds)
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 436 lines · 110 tokens per session scan A d40184a2ff38
pydicom is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,252 stars, last pushed 12d ago), licensed Apache-2.0. It adds 110 tokens to every session and 3,370 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to pydicom, differing in 8 lines, and is treated as a copy.
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