Agent skill

Review Paper

by Aperivue in Aperivue/medsci-skills

A skill your agent uses when writing a literature review article (narrative, scoping PRISMA-ScR or systematic).

MITAuto-check passedResearch & Science

Install Review Paper

skills CLI
$ npx skills add Aperivue/medsci-skills --skill review-paper -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Aperivue/medsci-skills review-paper --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Aperivue/medsci-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review-paper .claude/skills/review-paper && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review-paper
GitHub stars
333
Token cost
~1.3k tokens
SKILL.md length
619 words
Files
5 (incl. references)
Skills in repo
54
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when writing a literature review article (narrative, scoping PRISMA-ScR or systematic).

  • Works in 5 steps: Format + spine axis (the… → Scaffold the macro skeleton for the format → Summary-table stub (matched to type) → …
  • Writing a literature review article (narrative
  • SKILL.md covers Step 0 — Format + spine axis…, Step 1 — Scaffold the macro…, Step 2 — Summary-table stub… and Step 3 — Reporting +…, plus 2 more sections
  • Runs Python and Shell scripts from its folder

What it does

Review Paper is an agent skill from Aperivue/medsci-skills. Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Scaffolds a 7-part skeleton with a scope and non-overlap statement, summary-table stubs and reporting-guideline wiring, without inventing citations. Original research is /write-paper.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/macro_skeleton.md`, `skill.yml` and `tests/check_skeleton.py`).

It sits in Research & Science, covering ORMs and data access, Literature review and Project scaffolding. It works with Prisma. The repository describes itself as: Agent Skills for medical research — literature search, reporting-guideline & citation checks, statistics, publication figures, submission. Works with Claude Code, Codex, Cursor &… The licence is MIT.

When your agent uses it

  • Writing a literature review article (narrative
  • Scoping PRISMA-ScR

Example prompts

  • “/review-paper”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Format + spine axis (the structure-determining choice)
  2. Scaffold the macro skeleton for the format
  3. Summary-table stub (matched to type)
  4. Reporting + registration wiring
  5. QC hand-off

What it can do on your machine

Read from SKILL.md and the folder at commit 3b14ae2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python and Shell), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review Paper loads about 1.3k tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 72 tokens; SKILL.md has 619 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Aperivue/medsci-skills at commit 3b14ae2, republished under its MIT licence (© Aperivue). 619 words, ~1,291 tokens.

Download SKILL.mdSave it as .claude/skills/review-paper/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
review-paper
description
Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Scaffolds a 7-part skeleton with a scope and non-overlap statement, summary-table stubs and reporting-guideline wiring, without inventing citations. Original research is /write-paper.
metadata.triggers
review article, scoping review, narrative review, literature review, PRISMA-ScR, write a review

Review-Paper Skill

The review-article counterpart to write-paper (original research). For reviewing someone else's review article, use /peer-review or /self-review (the RV1-RV9 probes) instead.

Step 0 — Format + spine axis (the structure-determining choice)

  1. Confirm format with the user: narrative (SANRA) | scoping (PRISMA-ScR + JBI) | systematic (PRISMA 2020). This decides the reporting guideline and the registration path.
  2. 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.
  3. 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 macro skeleton for the format

Load ${CLAUDE_SKILL_DIR}/references/macro_skeleton.md and write the section for the chosen format to manuscript.md in the manuscript directory, with the summary-table stubs (Step 2) and that section's figure/table legend plan. The structure depends on the format:

  • Narrative — the 7-part skeleton below.
  • Scoping / systematic — IMRaD with one Methods and one Results slot per PRISMA-ScR or PRISMA 2020 item (the reference lists them by item number). Do not use the 7-part skeleton for these: it has no place for eligibility criteria, search, selection, charting/extraction, risk of bias or synthesis methods, nor for study-selection results. The thematic body by spine axis goes inside Results → synthesis; frontiers and the evaluation-metrics critique go inside Discussion.

The narrative 7-part skeleton:

  1. Abstract — a 4-5 move version (structured for scoping/systematic).
  2. Introduction — clinical motivation → technology → scope + non-overlap block (required field, all formats) → "this review…".
  3. Background / technical principles — tight; cite once, do not re-survey the field.
  4. Thematic body by spine axis — each section ends with a summary table (stub generated to match the type, Step 2).
  5. Frontiers / what is advancing.
  6. Challenges / discussion — include an evaluation-metrics critique subsection (a required quality signal: how the field measures itself, and where those metrics mislead).
  7. Conclusion — measured. A scoping review maps the evidence; it issues no recommendation-grade language or clinical recommendations.

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 not yet in the library, leave a [@NEW:short-topic] placeholder and route it to /search-lit; never fabricate a DOI, author, year, or citekey.

Show full SKILL.md (228 more words)Show less

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. Cells (study, year, metric, finding) are filled only from sources the user supplies or that are verified; an unknown cell stays a placeholder.

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 carry the chosen checklist (it bundles PRISMA-ScR and PRISMA 2020, not SANRA), 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:

  1. /self-review — the RV1-RV9 narrative-review probes auto-activate for a review article.
  2. /check-reporting — PRISMA-ScR or PRISMA 2020 (SANRA via the Step 3 manual table).
  3. /verify-refs — every citation resolves; 0 FABRICATED / MISMATCH.
  4. /humanize — AI-pattern density below threshold.
  5. /academic-aio — discoverability pass (optional).

Convergence gate — the draft is not done until: self-review fatal = 0; verify-refs FABRICATED/MISMATCH = 0; no [@NEW:...] placeholder citations remain; humanize density < 2.0.

Guards

  • Proportionate self-citation; declare an intellectual conflict of interest when an author has contributed to the area being reviewed.
  • Write only inside the manuscript directory.

© Aperivue, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/review-paper of Aperivue/medsci-skills.

  • SKILL.md
  • references/macro_skeleton.md
  • skill.yml
  • tests/check_skeleton.py
  • tests/test_macro_skeleton.sh

Open the folder on GitHubat commit 3b14ae2

Compare with similar skills

Review Paper next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review Paper compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Review Paper this skillAperivue/medsci-skills333—~1.3kAutomated safety check: PassMIT
Lit Searchluwill/research-skills862—~3.7kAutomated safety check: NotesMIT
Ma Search Bibliographyhtlin222/meta-pipe139—~2.1kAutomated safety check: NotesCustom licence
Lancet Reportingfranklee16/academic-research-skills2231 repos~1kAutomated safety check: PassNone
Nejm Reportingfranklee16/academic-research-skills2231 repos~993Automated safety check: PassNone
Psychbull Literature Search Strategyfranklee16/academic-research-skills2231 repos~908Automated safety check: PassNone

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Works with

Questions about Review Paper

What does Review Paper do?

A skill your agent uses when writing a literature review article (narrative, scoping PRISMA-ScR or systematic). Review Paper is an agent skill from Aperivue/medsci-skills. Use when writing a literature review article (narrative, scoping PRISMA-ScR or systematic).

When should I use Review Paper?

Review Paper fits situations like: writing a literature review article (narrative; scoping PRISMA-ScR.

How do I install Review Paper in Claude Code?

Run `npx skills add Aperivue/medsci-skills --skill review-paper -a claude-code`. Or copy the skill folder (skills/review-paper in Aperivue/medsci-skills) into .claude/skills/review-paper in your project. Claude Code loads it when a task matches its description.

How do I install Review Paper in Codex?

Run `npx skills add Aperivue/medsci-skills --skill review-paper -a codex`. Or copy the skill folder (skills/review-paper in Aperivue/medsci-skills) into .agents/skills/review-paper in your project. Codex loads it when a task matches its description.

Can I use Review Paper in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Aperivue/medsci-skills --skill review-paper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-paper, .gemini/skills/review-paper, .github/skills/review-paper and .opencode/skills/review-paper in your project.

What does Review Paper need to run?

Going by SKILL.md and its folder, Review Paper needs Python and a shell for the scripts in its folder. Our summary lists: Python 3; A Bash shell.

Does Review Paper access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Review Paper safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review Paper use?

Review Paper is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Paper use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.

What are the alternatives to Review Paper?

Skills that share tags, products or a category with Review Paper: Lit Search (luwill/research-skills, 862 stars), Ma Search Bibliography (htlin222/meta-pipe, 139 stars), Lancet Reporting (franklee16/academic-research-skills, 223 stars) and Nejm Reporting (franklee16/academic-research-skills, 223 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Paper?

Aperivue (a GitHub organization) maintains it in Aperivue/medsci-skills, which has 333 GitHub stars. The repository holds 54 skills in this directory. The repository was last updated on October 5, 2026.

Source: Aperivue/medsci-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.