What is imaging-data-commons?

A workflow for querying and downloading public cancer imaging data from the National Cancer Institute's Imaging Data Commons, a collection of cancer scans and related imaging records. It supports formats and modalities such as DICOM, CT, MR, PET, and pathology datasets.

Use it to search IDC collections, query imaging metadata, download datasets, access DICOM studies, visualize records, and assess whether data can be used for a project or AI training.

It helps locate suitable public imaging collections, inspect their metadata, view data, and check usage licences before downloading. Many access routes are available without authentication, while some optional services require cloud credentials.

imaging-data-commons — Skill by K-Dense-AI

Install

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.

agentmods

npx agentmods add skills/k-dense-ai/scientific-agent-skills/imaging-data-commons

Any agent

npx skills add K-Dense-AI/scientific-agent-skills --skill imaging-data-commons

Clone the repo

git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills

Made for: Claude Code, Codex.

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 7,180 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00075	$0.07180
Opus 5	$0.00037	$0.03590
Sonnet 5	$0.00015	$0.01436
Haiku 4.5	$0.00007	$0.00718

Measured yesterday against content hash 27ceb36b3ee1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

imaging-data-commons scanned grade A with 1 finding 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 yesterday.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/check_version.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

`curl`; do not install anything.** Installing costs ~77 MB of packaged index data plus

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

imaging-data-commons — 100% identical, 0 lines differ

skills/imaging-data-commons/SKILL.md · 497 lines

How it starts

The opening of the file, as written. The whole thing — 497 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Imaging Data Commons

Overview

Query and download public cancer imaging data from the National Cancer Institute Imaging Data Commons (IDC). No authentication required for data access.

Expected network access: IDC metadata is reachable three ways — a local DuckDB index shipped with the idc-index Python package (no network), or the hosted IDC service over MCP or REST (api.imaging.datacommons.cancer.gov, no authentication). File downloads use public GCS (storage.googleapis.com) and AWS S3 (s3.amazonaws.com) — no authentication required. DICOMweb access uses either the public IDC proxy (proxy.imaging.datacommons.cancer.gov, no auth) or the Google Cloud Healthcare API (healthcare.googleapis.com, requires GCP authentication). Optional BigQuery queries (bigquery.googleapis.com) also require GCP authentication. No credentials or environment variables are accessed by this skill.

Current IDC Data Version: v24 (always verify — see Best Practices)

Choose the access path first. There is no single default: the cheapest correct path depends on the session and the task.

Session already has the IDC MCP server? Route discovery and metadata there — see IDC MCP Server.
Otherwise, is idc-index installed? Run python scripts/check_version.py. If it passes, use idc-index for everything.
Not installed, and the task is read-only metadata — counts, attribute values, collection lookups, SQL under 10 000 rows, licenses, citations, viewer URLs? Use the REST API over curl; do not install anything. Installing costs ~77 MB of packaged index data plus pandas, pyarrow, and duckdb, which a metadata question does not need. See Data Access Options.
Not installed, and the task needs more than metadata — downloading files, pandas or plotting, pydicom/SimpleITK, pathology tiling, results past 10 000 rows, or a version-pinned script the user re-runs? Install idc-index: check_version.py exits non-zero and prints the exact install command for the running interpreter. Prefer a virtual environment, then restart Python.

Read the full file on GitHub · 497 lines

Files

What ships with it

14 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.

Changes

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.

yesterday First seen · 497 lines · 75 tokens per session scan A 27ceb36b3ee1

Subscribe to this mod's changes

imaging-data-commons is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (40,390 stars, last pushed yesterday), licensed MIT. It adds 75 tokens to every session and 7,180 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Productivity Research Scientific agent-skills ai-scientist bioinformatics chemoinformatics claude claude-skills

discovery-toolbox

A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…

dekan-aleksandr/biodiscovery-skills · 122 tokens

imaging-data-commons

Getting it into your agent

What it costs to keep this loaded

Grade A, and why

Makes network callslowCapability

Copies of this mod

How it starts

Imaging Data Commons

Overview

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

discovery-toolbox

alphafold-pocket-evaluator

pydeseq2-bulk-rna

scanpy-sc-analyzer

card-amr-profiler

diffdock-virtual-screener