Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
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 aipoch/medical-research-skills --skill medical-imaging-reviewgit clone --depth 1 https://github.com/aipoch/medical-research-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/aipoch/medical-research-skills/medical-imaging-review)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/medical-imaging-review"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/medical-imaging-review/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/aipoch/medical-research-skills/medical-imaging-review"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/medical-imaging-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00055 | $0.01195 |
| Opus 5 | $0.00028 | $0.00598 |
| Sonnet 5 | $0.00011 | $0.00239 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
medical-imaging-review 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Medical Imaging AI Literature Review Skill
Write comprehensive literature reviews following a systematic 7-phase workflow.
Quick Start
-
Initialize project with three core files:
CLAUDE.md- Writing guidelines and terminologyIMPLEMENTATION_PLAN.md- Staged execution planmanuscript_draft.md- Main manuscript
-
Follow the 7-phase workflow (see references/WORKFLOW.md)
-
Use domain-specific templates (see references/DOMAINS.md)
Core Principles
Writing Style
- Hedging language: "may", "suggests", "appears to", "has shown promising results"
- Avoid absolutes: Never say "X is the best method"
- Citation support: Every claim needs reference
- Limitations: Each method section needs a Limitations paragraph
Required Elements
- Key Points box (3-5 bullets) after title
- Comparison table for each major section
- Performance metrics: Dice (0.XXX), HD95 (X.XX mm)
- Figure placeholders with detailed captions
- References: 80-120 typical, organized by topic
Paragraph Structure
Topic sentence (main claim)
→ Supporting evidence (citations + data)
→ Analysis (critical evaluation)
→ Transition to next paragraph
Literature Sources
Use multi-source strategy for comprehensive coverage:
| Source | Best For | Tools |
|---|---|---|
| ArXiv | Latest DL methods, preprints | search_papers, read_paper |
| PubMed | Clinical validation, peer-reviewed | pubmed_search_articles |
| Zotero | Existing library, organized refs | zotero_search_items |
For MCP configuration details, see references/MCP_SETUP.md.
Standard Review Structure
# [Title]: State of the Art and Future Directions
## Key Points
- [3-5 bullets summarizing main findings]
## Abstract
## 1. Introduction
### 1.1 Clinical Background
### 1.2 Technical Challenges
### 1.3 Scope and Contributions
## 2. Datasets and Evaluation Metrics
### 2.1 Public Datasets (Table 1)
### 2.2 Evaluation Metrics
## 3. Deep Learning Methods
### 3.1 [Category 1]
### 3.2 [Category 2]
(Table 2: Method Comparison)
## 4. Downstream Applications
## 5. Commercial Products & Clinical Translation (Table 3)
## 6. Discussion
### 6.1 Current Limitations
### 6.2 Future Directions
## 7. Conclusion
## Input Validation
This skill accepts requests that match the documented purpose of `medical-imaging-review` and include enough context to complete the workflow safely.
Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:
> `medical-imaging-review` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
## References
What ships with it
7 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 · 166 lines · 55 tokens per session scan A 1bfedad3e699
medical-imaging-review is a skill published in the GitHub repository aipoch/medical-research-skills (1,869 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 1,195 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.
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