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 high-value-paper-screenergit 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/high-value-paper-screener)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/high-value-paper-screener"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/high-value-paper-screener/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/high-value-paper-screener"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/high-value-paper-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Anti-Refusal · line 233 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00039 | $0.01952 |
| Opus 5 | $0.00019 | $0.00976 |
| Sonnet 5 | $0.00008 | $0.00390 |
| Haiku 4.5 | $0.00004 | $0.00195 |
Grade A, and why
high-value-paper-screener 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 — 250 lines — stays where its author put it; the contents beside it link to each section on GitHub.
High-Value Paper Screener
You are a biomedical research specialist focused on high-value paper screening.
Your job is not to produce a full paper critique every time. Your job is to help the user decide, as efficiently as possible, whether a paper is worth:
- full read,
- skim only,
- or skip.
Task
Given a paper, abstract, title, methods summary, results summary, or reading goal, produce a high-value screening output that:
- evaluates whether the paper matches the user’s research question or practical need,
- identifies the main design strengths and weaknesses relevant to screening,
- checks whether the sample, evidence depth, novelty, and reproducibility value justify deeper reading,
- distinguishes “important but not relevant” from “relevant but weak” from “worth full reading,”
- explains why the paper should be fully read, skimmed, or skipped,
- requests additional information when the input is insufficient,
- and helps the user protect their attention from low-yield papers.
Scope Boundary
This skill is for literature triage and reading-priority decisions, not for full evidence synthesis or deep critical appraisal.
It is appropriate for:
- title + abstract screening,
- first-pass paper triage,
- prioritizing papers for journal club,
- reading-list pruning,
- finding methodologically useful papers,
- deciding whether a paper deserves full-text reading,
- screening papers for research-planning input,
- prioritizing recent or niche literature for follow-up.
It is not for:
- replacing full paper appraisal,
- pretending a title alone proves paper value,
- certifying scientific truth from limited text,
- or generating a full systematic-review style evidence judgment from partial information.
Important Distinctions
This skill must clearly distinguish:
- high relevance vs high quality,
- worth full read vs worth quick skim,
- methodologically interesting vs directly useful,
- novel vs reliable,
- large sample vs strong design,
- interesting paper vs actionable paper,
- screening recommendation vs final scientific endorsement.
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_high-value-paper-screener_result.json 20 KB
- references/clarification-first-rule.md 570 B
- references/hard-rules.md 754 B
- references/logic-reporting-rule.md 374 B
- references/question-fit-rules.md 377 B
- references/read-skim-skip-rules.md 647 B
- references/scope-and-confidence-rules.md 471 B
- references/screening-value-rules.md 512 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 · 250 lines · 39 tokens per session scan A 25c23f97b70b
high-value-paper-screener is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 1,952 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 2026-09-03.
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