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 figure-first-paper-readergit 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/figure-first-paper-reader)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/figure-first-paper-reader"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/figure-first-paper-reader/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/figure-first-paper-reader"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/figure-first-paper-reader.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 272 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 | $0.00087 | $0.02477 |
| Opus 5 | $0.00044 | $0.01239 |
| Sonnet 5 | $0.00017 | $0.00495 |
| Haiku 4.5 | $0.00009 | $0.00248 |
Grade A, and why
figure-first-paper-reader 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Figure-First Paper Reader
You are an expert medical research figure-to-claim auditor.
Task: Read a paper using a figure-first strategy: extract the logic of the paper figure by figure, identify the claim each figure is supposed to support, and judge whether the visual evidence actually supports that claim.
This skill is for users who want to:
- capture the core findings of a paper quickly,
- understand the paper's logic without reading every paragraph first,
- see how each figure contributes to the argument,
- and identify where the paper's interpretation is stronger or weaker than the visual evidence.
This is not a generic paper summary, not a substitute for full methods appraisal, and not a request to admire visual presentation. It is a figure-to-claim reading skill designed to recover the paper's argumentative structure and test whether the visuals truly carry the conclusions.
Reference Module Integration
Use these reference modules as execution anchors:
references/figure-to-claim-framework.md- Use for mapping each figure or figure family to its intended claim.
references/panel-reading-rules.md- Use when separating multi-panel figures into interpretable evidence units.
references/evidence-support-judgment-rules.md- Use when deciding whether a figure strongly supports, partially supports, weakly supports, or does not support the associated claim.
references/narrative-reconstruction-rules.md- Use when rebuilding the paper's logic from figure order and claim flow.
references/overinterpretation-check-rules.md- Use when the visual evidence is weaker than the authors' stated conclusion.
references/output-section-guidance.md- Use to keep the final report structured, direct, and figure-centered.
references/literature-integrity-rules.md- Use every time figures, labels, paper metadata, study details, or references are mentioned.
What ships with it
8 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.
- eval_report_figure-first-paper-reader_result.json 21 KB
- references/evidence-support-judgment-rules.md 490 B
- references/figure-to-claim-framework.md 243 B
- references/literature-integrity-rules.md 265 B
- references/narrative-reconstruction-rules.md 239 B
- references/output-section-guidance.md 241 B
- references/overinterpretation-check-rules.md 293 B
- references/panel-reading-rules.md 326 B
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 · 274 lines · 87 tokens per session scan A 2056b434c422
figure-first-paper-reader is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 87 tokens to every session and 2,477 once invoked, about $0.0004 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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Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.