mcpbeat

Review Paper

aperivue/review-paper

> Scaffold and draft medical/AI literature reviews (narrative, scoping PRISMA-ScR, or systematic). Asks for the spine axis, builds a 7-part skeleton with a required Intro scope/non-overlap block, a summary-table stub, an evaluation-metrics critique subsection, and reporting-guideline wiring. Reuses the self-review RV1-RV9 narrative-review probes for QC. Does not invent citations.

2k tokens
context cost
the whole folder, loaded on every use
3
files
instructions only
0
copies elsewhere
how many repositories repackaged it
230
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Aperivue/medsci-skills --skill review-paper

The instruction itself

9 sections, as written by the author

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-review reports 0

fatal findings and /verify-refs reports 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).

Step 1 — Scaffold the 7-part macro skeleton

Load ${CLAUDE_SKILL_DIR}/references/macro_skeleton.md and instantiate:

  • Abstract — structured for scoping/systematic; a 4-5 move version for narrative.
  • Introduction — clinical motivation → technology → **scope + non-overlap block

(required field)** → "this review…".

  • Background / technical principles — tight; cite once, do not re-survey the field.
  • Thematic body by spine axis — each section ends with a summary table (stub

generated to match the type, Step 2).

  • Frontiers / what is advancing.
  • Challenges / discussion — include an evaluation-metrics critique subsection (a

required quality signal: how the field measures itself, and where those metrics mislead).

  • Conclusion — measured; no recommendation-grade language for a scoping review.

Step 2 — Summary-table stub (matched to type)

  • Narrative / scoping: study | year | [spine-axis value] | method | key finding.
  • Systematic: PRISMA flow + a study-characteristics table + an extraction table.

The stub ships with column headers and one placeholder row; rows are filled only from

verified sources (see Anti-Hallucination).

Step 3 — Reporting + registration wiring

  • Scoping → PRISMA-ScR (+ JBI charting) + OSF registration.
  • Narrative → SANRA (a 6-item appraisal aid, not a reporting checklist — do not

over-enforce it).

  • Systematic → PRISMA 2020 (+ PROSPERO registration).
  • If /check-reporting does not yet carry the chosen checklist (e.g. PRISMA-ScR), track a

manual gap table and flag it for the user rather than silently skipping the item.

Step 4 — QC hand-off

Run the standard manuscript QC chain, which this skill is designed to feed:

  • /self-review — the RV1-RV9 narrative-review probes auto-activate for a review article.
  • /check-reporting — the chosen guideline (SANRA / PRISMA-ScR / PRISMA 2020).
  • /verify-refs — every citation resolves; 0 FABRICATED / MISMATCH.
  • /humanize — AI-pattern density below threshold.
  • /academic-aio — discoverability pass (optional).

Convergence gate: self-review fatal = 0; verify-refs FABRICATED/MISMATCH = 0; no

[NEEDS-REF] / [@NEW:]-style placeholder citations remain; humanize density < 2.0.

Guards

  • Citations resolve to _src/refs.bib only; never invent citekeys (see Anti-Hallucination).
  • Proportionate self-citation; declare an intellectual conflict of interest when an author

has contributed to the area being reviewed (per intellectual-coi).

  • Write only inside the manuscript directory.

references/

  • macro_skeleton.md — the 7-part template and the table/figure plan per review type.

How to use it

Copy the folder

Take aperivue/review-paper from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.