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 Aperivue/medsci-skills --skill review-papergit clone --depth 1 https://github.com/Aperivue/medsci-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/aperivue/medsci-skills/review-paper)<a href="https://agentmods.dev/skills/aperivue/medsci-skills/review-paper"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/review-paper/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/aperivue/medsci-skills/review-paper"><img src="https://agentmods.dev/badge/skills/aperivue/medsci-skills/review-paper.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 | $0.00091 | $0.01437 |
| Opus 5 | $0.00046 | $0.00718 |
| Sonnet 5 | $0.00018 | $0.00287 |
| Haiku 4.5 | $0.00009 | $0.00144 |
Grade A, and why
review-paper 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 12d 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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review-Paper Skill
Scaffold and draft a literature review — narrative, scoping (PRISMA-ScR), or systematic
(PRISMA 2020) — for medical / medical-AI research. This skill builds the structure, the
required scope/non-overlap framing, the summary-table stubs, and the reporting-guideline
wiring, then hands off to the existing QC skills. It is the review-article counterpart to
write-paper (which targets original research); for reviewing someone else's review
article, use /peer-review or /self-review (the RV1-RV9 probes). The structure follows
established review-writing conventions; it is not derived from, and does not reproduce, any
specific published review.
Anti-Hallucination
- Never invent citations. Every citekey must resolve to the project's verified
_src/refs.bib(produced by/search-lit→/lit-sync→/verify-refs). If a claim needs a reference that is not yet in the library, leave a[NEEDS-REF: claim]marker and route it to/search-lit; do not fabricate a DOI, author, year, or citekey. - Never invent data. Summary-table cells (study, year, metric, finding) are filled only from sources the user supplies or that are verified; an unknown cell stays a placeholder.
- No recommendation-grade language without standing. For a scoping review especially, the output maps the evidence — it does not issue clinical recommendations.
- Quality gate before hand-off: the draft is not "done" until
/self-reviewreports 0 fatal findings and/verify-refsreports 0 FABRICATED / MISMATCH and no placeholder citations remain.
Step 0 — Format + spine axis (the structure-determining choice)
- Confirm format with the user: narrative (SANRA) | scoping (PRISMA-ScR + JBI) | systematic (PRISMA 2020). This decides the reporting guideline and the registration path.
- Choose the spine axis — the single most consequential decision: organize the body by modality (e.g. 2D → 3D), by task (generation / QA / deployment), or by lifecycle stage. Every body section then follows this one axis; mixing axes is the most common structural failure.
- Require a scope statement + non-overlap boundary against prior/adjacent reviews — this pre-empts the reviewer's first question, "why another review on this?" (user-approval checkpoint: confirm the boundary with the user before scaffolding).
What ships with it
2 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.
- 12d ago First seen · 105 lines · 91 tokens per session scan A 3d7b038cfd42
review-paper is a skill published in the GitHub repository Aperivue/medsci-skills (292 stars, last pushed 4d ago), licensed MIT. It adds 91 tokens to every session and 1,437 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
clinical-trials-search
Search ClinicalTrials.gov with natural language queries. Find clinical trials, enrollment, and outcomes using Valyu semantic search.
shidi
A Chinese-language research assistant role that turns a user’s ideas into literature reviews, experiment plans, figures and organised data.
clinical-research
Use when designing a prospective clinical study before submission — selecting and classifying endpoints (primary / key-secondary / exploratory, with surrogate-endpoint flagging), estimating sample size and power for two-arm designs (means / proportions / survival), or scoring a study plan for feasibility and a GO /…
sr-search-record
An automated literature-review search and screening workflow using OpenAlex, an open database and API for scholarly research, and Zotero, a reference manager.
critical-paper-reading
A paper-reading workflow for critically examining one research paper from a PDF or Zotero item. Zotero is a tool for organising research papers and references.
knowledge-module-gen
A workflow for generating knowledge-module files from a list of academic reading modules. It reads full papers from Zotero, NotebookLM, or local PDFs and records page references and execution checks.