radiology-report-analysis

radiology-report-analysis is a skill for Claude Code, Codex from aizech/clinical-skills. It costs 57 tokens per session (2,810 once invoked), scanned A, original, MIT.

A guide for reading radiology reports, which describe medical scans such as X-rays, CT scans, or MRI scans. It extracts findings, measurements, impressions, and recommendations from structured or free-text reports.

In plain words
What is it for?
Summarizing reports, extracting measurements and findings, identifying critical results, checking report quality, and reviewing report text.
Why use it?
It turns reports into organized information and supports review for key findings and report quality. It also separates the report's observations from its overall impression.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Summarizing reports, extracting measurements and findings, identifying critical results, checking report quality, and reviewing report text.

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Install with agentmods
npx agentmods add skills/aizech/clinical-skills/radiology-report-analysis
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.

Any agent
npx skills add aizech/clinical-skills --skill radiology-report-analysis
Clone the repo
git clone --depth 1 https://github.com/aizech/clinical-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for radiology-report-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/aizech/clinical-skills/radiology-report-analysis/github.svg)](https://agentmods.dev/skills/aizech/clinical-skills/radiology-report-analysis)
Your own site
<a href="https://agentmods.dev/skills/aizech/clinical-skills/radiology-report-analysis"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/radiology-report-analysis/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.

agentmods 80×15 button for radiology-report-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/aizech/clinical-skills/radiology-report-analysis"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/radiology-report-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,810 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00057 $0.02810
Opus 5 $0.00028 $0.01405
Sonnet 5 $0.00011 $0.00562
Haiku 4.5 $0.00006 $0.00281

Measured 11d ago against content hash aaf66b5a0ba9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

radiology-report-analysis 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 11d 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.

.agents/skills/radiology-report-analysis/SKILL.md · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Radiology Report Analysis

You are a radiology report analysis expert. Your role is to extract, interpret, and structure information from radiology reports.

Report Structure

Standard Report Sections

RADIOLOGY REPORT
├── Header Information
│   ├── Patient ID
│   ├── Study Date
│   ├── Modality
│   ├── Referring Physician
│   └── Accession Number
├── Clinical History
├── Examination/Study Description
├── Findings
│   ├── Organ System 1
│   ├── Organ System 2
│   └── ...
└── Impression
    ├── Primary Finding (numbered)
    ├── Secondary Finding
    └── Recommendations

Extraction Patterns

Findings Extraction

Extract findings from free-text reports:

def extract_findings(report_text):
    sections = parse_report_sections(report_text)
    findings = []
    
    # Pattern: Finding descriptions often start with bullets, numbers, or organ names
    finding_patterns = [
        r'[-•]\s*(.+)',           # Bullet points
        r'\d+\.\s+([A-Z][^:]+):\s*(.+)',  # Numbered with colon
        r'([A-Z][a-z]+(?:\s+[a-z]+)?):\s*(.+)',  # Organ: description
    ]
    
    for pattern in finding_patterns:
        matches = re.finditer(pattern, report_text)
        for match in matches:
            findings.append({
                'organ': extract_organ(match),
                'description': match.group(1) if match.lastindex else match.group(0),
                'severity': classify_severity(match)
            })
    
    return findings

Impression Extraction

def extract_impression(report_text):
    # Look for IMPRESSION section
    impression_pattern = r'IMPRESSION[:\s]+(.+?)(?:\n\n|\Z)'
    match = re.search(impression_pattern, report_text, re.DOTALL | re.IGNORECASE)
    
    if match:
        impression_text = match.group(1)
        # Parse numbered impressions
        impressions = re.findall(r'\d+\.\s*(.+?)(?=\n\d+\.|\Z)', impression_text)
        return impressions
    
    # Fallback: last paragraph is often impression
    paragraphs = report_text.split('\n\n')
    return [paragraphs[-1]] if paragraphs else []

Read the full file on GitHub · 371 lines

Files

What ships with it

1 file 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.

  1. 11d ago First seen · 371 lines · 57 tokens per session scan A aaf66b5a0ba9

Subscribe to this mod's changes

radiology-report-analysis is a skill published in the GitHub repository aizech/clinical-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 57 tokens to every session and 2,810 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 2026-08-31.

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