Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill pydicomgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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/k-dense-ai/scientific-agent-skills/pydicom)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/pydicom"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-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/k-dense-ai/scientific-agent-skills/pydicom"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/pydicom.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 295 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00056 | $0.04117 |
| Opus 5 | $0.00028 | $0.02058 |
| Sonnet 5 | $0.00011 | $0.00823 |
| Haiku 4.5 | $0.00006 | $0.00412 |
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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pydicom
Use pydicom for DICOM dataset I/O and pixel processing. Version 3.0.2 is the
current stable release reviewed here. It fixes CVE-2026-32711, a crafted
DICOMDIR path-traversal issue. pydicom 3.0.2 declares Python >=3.10; its
bundled DICOM dictionary is 2024c, while the live DICOM Standard may be newer.
Mandatory safety boundary
- Work only with local data that the user is authorized to access.
- DICOM metadata, file names, private elements, overlays, structured content, and pixels may contain protected health information (PHI).
- Never print
Dataset, export full metadata/JSON, or log element values by default. Use a documented allowlist and aggregate output. - pydicom is a general DICOM framework, not a diagnostic viewer. Pixel output, validation, conversion, and plugin availability are not diagnostic claims.
- De-identification is profile-, purpose-, recipient-, jurisdiction-, and threat-context-specific. It requires privacy/DICOM expert verification.
- Never claim that a tag-removal script is DICOM PS3.15, HIPAA, GDPR, or other compliance. Preserve originals and audit derived outputs.
- Treat deterministic pseudonymization keys and UID maps as re-identification secrets: use least privilege and encrypted/managed secret storage, never commit, sync, log, or share them with derivatives, and define backup, rotation, revocation, and destruction procedures. A leaked key invalidates the intended separation; rotation also changes deterministic mappings.
- Set explicit input-file, file-count, frame-count, decoded-byte, and output limits before parsing untrusted or unusually large datasets.
Installation
Create or activate an isolated environment, then install the exact reviewed release:
uv pip install "pydicom==3.0.2"
Uncompressed pixel arrays and image rendering:
uv pip install "pydicom==3.0.2" "numpy==2.5.1" "Pillow==12.3.0"
Install only the transfer-syntax plugins required by the deployment:
# JPEG/JPEG-LS, JPEG 2000/HTJ2K, and faster RLE through pylibjpeg
uv pip install "numpy==2.5.1" "pylibjpeg==2.1.0" \
"pylibjpeg-libjpeg==2.4.0" "pylibjpeg-openjpeg==2.5.0" \
"pylibjpeg-rle==2.2.0"
# JPEG-LS encoder/decoder
uv pip install "numpy==2.5.1" "pyjpegls==1.5.1"
# Alternative decoder with platform-specific wheels
uv pip install "python-gdcm==3.2.6"
What ships with it
12 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.
- references/common_tags.md 12 KB
- references/transfer_syntaxes.md 12 KB
- scripts/__init__.py 60 B runs code
- scripts/_common.py 29 KB runs code
- scripts/anonymize_dicom.py 25 KB runs code
- scripts/deidentification_audit.py 13 KB runs code
- scripts/dicom_inventory.py 13 KB runs code
- scripts/dicom_to_image.py 15 KB runs code
- scripts/extract_metadata.py 11 KB runs code
- scripts/pixel_frame_planner.py 9.9 KB runs code
- scripts/transfer_syntax_inspector.py 7.7 KB runs code
- scripts/uid_mapping_validator.py 8.3 KB runs code
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.
- 8d ago First seen · 399 lines · 56 tokens per session scan A 3c8d3a5880d5
pydicom is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,469 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 4,117 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
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digital-twin-discharge-drafter
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discharge-summary-writer
Generate hospital discharge summaries from admission data, hospital course, diagnoses, procedures, and follow-up plans; use when a structured discharge document is required from clinical notes.
synthesize
Thesis report synthesis — turn a thesis's markdown artifacts into its letter-size thesis-report.html, then OPTIMIZE it against real page renders. Four-step loop — pack (deterministic Python bundle of all sources + report/metrics.json), author (the LLM writes report/content.html — narrative, KPI tiles, badges…
figure-duplicate-audit
A review of scientific figure images for duplicated, reused, altered, or uninformative panels. Scientific figures are the charts, photographs, and image panels included in research papers.
LaTeX工具
A tool for creating, compiling, and checking mathematical modelling papers written in LaTeX, a document system often used for technical writing.