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 aizech/clinical-skills --skill radiology-researchgit clone --depth 1 https://github.com/aizech/clinical-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/aizech/clinical-skills/radiology-research)<a href="https://agentmods.dev/skills/aizech/clinical-skills/radiology-research"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/radiology-research/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/aizech/clinical-skills/radiology-research"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/radiology-research.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 | $0.00044 | $0.00558 |
| Opus 5 | $0.00022 | $0.00279 |
| Sonnet 5 | $0.00009 | $0.00112 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
radiology-research 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.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Radiology Research Skill
Triggers
- "recent research on"
- "literature review"
- "published studies"
- "evidence for"
- "systematic review"
- "clinical trials"
- "accuracy metrics"
- "what does the evidence say"
Parameters
research_type(required): Type of research queryrecent_papers- Latest publicationsevidence_summary- Synthesized evidenceaccuracy_metrics- Performance benchmarksguidelines_review- Professional society guidelinesclinical_trials- Ongoing trialssystematic_review- Comprehensive literature review
topic(required): Research topic or clinical questiontime_range(optional): Publication date filter (e.g., last 2 years)modality(optional): Specific imaging modality
Research Quality Levels
| Level | Evidence Type |
|---|---|
| 1 | Randomized controlled trials, meta-analyses |
| 2 | Cohort studies, case-control |
| 3 | Case series, expert opinion |
| 4 | Anecdotal reports |
Key Research Areas
AI/ML in Radiology
- Diagnostic accuracy studies
- Performance benchmarking
- External validation results
- Clinical implementation outcomes
Imaging Techniques
- Protocol optimization
- New sequence development
- Contrast agent innovations
- Dose reduction techniques
Clinical Applications
- Screening effectiveness
- Diagnostic accuracy by condition
- Treatment monitoring
- Prognostic imaging markers
Literature Sources
- PubMed/MEDLINE (primary)
- RSNA Radiology (journal)
- Academic Radiology (journal)
- European Radiology (journal)
- arXiv (preprints)
- ClinicalTrials.gov (trials)
Output Format
Returns structured JSON with:
- Citation list with relevance scores
- Key findings summary
- Accuracy metrics (sensitivity, specificity, AUC)
- Study quality indicators
- Clinical applicability notes
Usage Examples
research_type: recent_papers
topic: deep learning chest X-ray pneumonia
time_range: last_2_years
research_type: evidence_summary
topic: MRI vs CT for appendicitis diagnosis
modality: CT, MRI
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.
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.
- 11d ago First seen · 97 lines · 44 tokens per session scan A 8366b00ad0ac
radiology-research is a skill published in the GitHub repository aizech/clinical-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 558 once invoked, about $0.0002 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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