Literature Review
neflibata-feng/MyArxiv-Agent
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.).
Retrieve, verify, and synthesize scientific literature. An agent skill from xuzhougeng/wisp-science.
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install xuzhougeng/wisp-science literature-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/literature-review .claude/skills/literature-review && rm -rf skills-srcUse ~/.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/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .claude/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install xuzhougeng/wisp-science literature-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/literature-review .agents/skills/literature-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .agents/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install xuzhougeng/wisp-science literature-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/literature-review .cursor/skills/literature-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .cursor/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/xuzhougeng/wisp-science.git --path skills/literature-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install xuzhougeng/wisp-science literature-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/literature-review .gemini/skills/literature-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .gemini/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install xuzhougeng/wisp-science literature-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/literature-review .github/skills/literature-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .github/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add xuzhougeng/wisp-science --skill literature-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install xuzhougeng/wisp-science literature-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/xuzhougeng/wisp-science.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/literature-review .opencode/skills/literature-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "literature-review" agent skill from https://github.com/xuzhougeng/wisp-science/tree/main/skills/literature-review into .opencode/skills/literature-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "literature-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
literature-reviewRetrieve, verify, and synthesize scientific literature. An agent skill from xuzhougeng/wisp-science.
Literature Review is an agent skill from xuzhougeng/wisp-science. Retrieve, verify, and synthesize scientific literature. Use for seminal-paper lookups, evidence summaries, method comparisons, and gap analyses. Every citation must come from a live lookup, never from memory; retractions are checked; the deliverable is argued prose with resolvable DOI links.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `runtime.py`).
It sits in Research & Science, covering Academic paper search, Literature review and Citation management. The repository describes itself as: Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformatics tools, SSH/WSL/GPU runtimes, and OpenAI/Anthropic models. The licence is Apache-2.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 2ba143b. It shows what the files ask for, not the result of running them.
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.
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
doi.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Literature Review loads about 1.7k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 802 words of instructions outside code blocks.
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.
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.
The full file from xuzhougeng/wisp-science at commit 2ba143b, republished under its Apache-2.0 licence (© xuzhougeng). 802 words, ~1,690 tokens.
.claude/skills/literature-review/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Work through six steps: scope, sweep, expand, verify, write, lint. The failure modes this skill exists to prevent are all silent — a fabricated DOI, a retracted headline result, a reading list dressed up as a synthesis — so each step below names the check that catches it.
Different phrasings want different deliverables:
| Request shape | Deliverable |
|---|---|
| "the paper for X" / "the original/seminal…" | one or two primary citations |
| "what's the evidence on X" | thematic synthesis |
| "compare A and B" | trade-off analysis ending in a recommendation |
| "where are the gaps" | named gaps, each anchored to what establishes it |
A vague lay query gets the scope a domain expert would default to, stated explicitly ("taking this as human RCT evidence; animal work is separate"). Clarify with the user only when the answer would change what you retrieve.
Never write from recall. Recall chooses the framing and the search terms;
retrieval supplies every citation. Start with search_openalex /
crossref_lookup from this skill's runtime.py, a PubMed query, or any
literature connector advertised in the session (search_skills with
{"query":"literature PubMed Semantic Scholar bioRxiv ClinicalTrials"} finds
installed guidance; load matches with use_skill).
For a named-paper lookup, the target is the highly cited primary publication that later work cites — not a review of it, not a news piece. Even when you know the paper cold, resolving its DOI is one tool call; skipping it turns a citation into a claim about a citation.
Keyword sweeps miss two things systematically: the foundational paper a field
builds on, and the newest work that extends or contests your top hits. Take
the two or three most relevant results and run expand_citations(doi) — it
returns references (backward) and cited-by (forward) from OpenAlex. Fold the
on-topic finds back into the working set before drafting. A survey-grade
answer typically rests on fifteen or more distinct primary-paper DOIs; a
handful of reviews is a reading list.
The Python OpenAlex helpers raise on HTTP errors, timeouts, or malformed responses. Empty results are valid only after successful retrieval. If either citation direction fails, report the retrieval failure rather than treating the partial graph as complete. Do not convert an exception into an empty list.
Run verify_dois on everything you intend to cite. Distinguish registered,
not resolving, and unverified (ok=None, e.g. network failure) results. A
registered DOI still requires reading the paper to check whether it supports
the claim; a failed request is not evidence of fabrication. When you have
author/year/journal but no DOI, look it up; never
pattern-complete one. For surprising or high-profile findings, check
Crossref's update-to field: sensational papers are findable because they
were sensational, and some were retracted. When the requested paper does not
exist — the claim collapsed or was never established — say exactly that and
point at what the evidence actually shows, instead of substituting the
nearest-matching citation.
Organize by question or theme, never paper-by-paper. The value is the layer on top of the papers: what replicated, what didn't, where the field agrees on effect but splits on mechanism, which older result a newer one superseded. Two tests for the draft:
- Author Year showed… are a
paragraph you haven't written. Bullets are for genuinely enumerable things
(a reference appendix, a comparison table); the argument itself is prose.Calibrate stated confidence to the evidence: a phase-3 RCT is stated plainly, a single-cohort finding is "one group reported", preprints are flagged as preprints, contested areas get both sides plus an honest "unresolved". Engage a contested premise rather than building on it.
Cite inline as [Author Year](https://doi.org/10.xxxx/...) so prose renders
as (Author Year) with the DOI in the href. URL-encode parentheses inside a
DOI as %28/%29. No numbered [1] references — they desync on reorder.
Headings are short noun phrases; with five or more topics, group under two or
three ## and demote the rest to ###.
The answer lives in the chat reply: open on the finding itself, lay out the evidence with inline DOIs, close on what remains open. For anything beyond a one-paper lookup, also save the full review to a project-relative Markdown file and link it at the end of the reply. Process narration — "all DOIs verified", "no retraction flags", "report saved" — belongs nowhere: not as opener, footer, or subtitle. Verification lives in the tool trace.
Before saving, run style_pass(draft) from runtime.py once on the full
markdown, fix what it lists in one editing pass, and save. It is a lint, not
a gate — do not loop on it. If style_pass is not defined in the kernel,
read this skill's runtime.py and exec it first.
© xuzhougeng, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/literature-review of xuzhougeng/wisp-science.
Open the folder on GitHubat commit 2ba143b
Literature Review 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Literature Review this skillxuzhougeng/wisp-science | 1k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Literature Reviewneflibata-feng/MyArxiv-Agent | 126 | 20 repos | ~5.9k | Automated safety check: Notes | MIT | |
| Preprint Search on bioRxivLigphiDonk/Oh-my--paper | 739 | 12 repos | ~3.7k | Automated safety check: Pass | MIT | |
| Systematic Literature Review Builderbytedance/deer-flow | 84k | 2 repos | ~4.3k | Automated safety check: Pass | MIT | |
| Paper Research on arXivXiaomiMiMo/MiMo-Code | 14k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Literature Review AgentAr9av/PaperOrchestra | 679 | 1 repos | ~5.2k | Automated safety check: Pass | Custom licence |
neflibata-feng/MyArxiv-Agent
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.).
LigphiDonk/Oh-my--paper
Searches bioRxiv life sciences preprints by keyword, author, date range or category with a Python script, returning JSON metadata and optional PDF downloads.
bytedance/deer-flow
Searches arXiv across many papers on one topic, extracts each paper's methodology and findings in parallel, and synthesizes a cited literature review.
XiaomiMiMo/MiMo-Code
Searches arXiv, fetches metadata, generates BibTeX, downloads PDFs and finds citations and related papers using a bundled Python script.
Ar9av/PaperOrchestra
Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). An agent skill from Ar9av/PaperOrchestra.
federicodeponte/opendraft
An 18-agent pipeline that turns one topic line into a drafted research paper, literature review, or thesis chapter.
xuzhougeng/wisp-science
A skill your agent uses when designing, reviewing, or implementing single-cell RNA-seq QC in Python or R with a human-in-the-loop, data-driven approach.
xuzhougeng/wisp-science
学术审查 / research-integrity screening of a manuscript's figures and reported numbers.
xuzhougeng/wisp-science
将概念、理论或分析方法类图书蒸馏为证据可追溯、经人工门禁审核且不暴露书名、作者、出版社等来源身份的任务型 Skill 候选。用于新建或恢复图书蒸馏、以本地 Tesseract 扫描 DOCX 全部内嵌图像或 Poppler 渲染的扫描 PDF 全页、建立 source map 与 evidence/claim/relation/capability…
xuzhougeng/wisp-science
Create, update, validate, and evaluate Wisp skills. An agent skill from xuzhougeng/wisp-science.
xuzhougeng/wisp-science
Build, audit, authorize, recover, or finalize dynamic Zotero citations and bibliographies in Microsoft Word DOCX files with a protected-source, digest-bound workflow.
xuzhougeng/wisp-science
Set up and validate a reproducible Python or R environment on a Wisp execution context.
Categories
Retrieve, verify, and synthesize scientific literature. An agent skill from xuzhougeng/wisp-science. Literature Review is an agent skill from xuzhougeng/wisp-science. Retrieve, verify, and synthesize scientific literature.
Literature Review fits situations like: seminal-paper lookups; evidence summaries; method comparisons.
Run `npx skills add xuzhougeng/wisp-science --skill literature-review -a claude-code`. Or copy the skill folder (skills/literature-review in xuzhougeng/wisp-science) into .claude/skills/literature-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add xuzhougeng/wisp-science --skill literature-review -a codex`. Or copy the skill folder (skills/literature-review in xuzhougeng/wisp-science) into .agents/skills/literature-review in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xuzhougeng/wisp-science --skill literature-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/literature-review, .gemini/skills/literature-review, .github/skills/literature-review and .opencode/skills/literature-review in your project.
Going by SKILL.md and its folder, Literature Review needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md names 1 domain. In commands or code: doi.org; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
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.
Literature Review is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Literature Review: Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars), Preprint Search on bioRxiv (LigphiDonk/Oh-my--paper, 739 stars), Systematic Literature Review Builder (bytedance/deer-flow, 84k stars) and Paper Research on arXiv (XiaomiMiMo/MiMo-Code, 14k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
xuzhougeng (a GitHub user) maintains it in xuzhougeng/wisp-science, which has 1,026 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 10, 2026.
Source: xuzhougeng/wisp-science on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.