literature-review
Skill0 starsChanged 5 days agoApache-2.0View on GitHub
Turn a research question into a bounded, reproducible review: search four indexes, check sufficiency, screen records, then seal a report.
88 other projects use a version of this.
Adopted by
Most recently taken up by
- lengrufeng2008/dsh-skill-librarytheir own version, first seen Nov 15, 2026
- ranveerankhira-gif/research-agent-skills-zhtheir own version, first seen Nov 15, 2026
- xiong-zx/skillstheir own version, first seen Nov 15, 2026
- delorenj/skillstheir own version, first seen Nov 8, 2026
- DAAF-Contribution-Community/daaftheir own version, first seen Nov 8, 2026
- HughYau/AcademicForgetheir own version, first seen Nov 8, 2026
Used with
Projects with it also use pdf-explore, paper-narrative and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
JimLiuSkillpdf-explore
Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers — including appendices). Skip it only for a single lookup of 1–4 pages quoted in your very next response — `read_file(pages=[...])` attaches pages as images that are dropped from context after one turn, so multi-section answers end up re-reading the same ranges repeatedly. Parses the PDF once in the Python kernel: `pdf_pages` (pages as persistent text), `pdf_outline` (TOC), `pdf_scan` (rank pages by relevance), `pdf_map`/`pdf_extract` (per-page summary / structured fields via parallel haiku calls). For PDF creation/manipulation, use reportlab/pypdf directly.
Also in 9 projects that use this
JimLiuSkillpaper-narrative
Judge and reshape the STORY a paper's figures tell. Input is the work itself — manuscript (or abstract) + figure deck — no hand-written brief. `derive_paper_brief(abstract, captions)` extracts pitch/vision/per-figure-claims; a handling-editor reviewer on the full deck returns hook_verdict (would Fig 1 make me send this for review?), arc (hook→mechanism→evidence→application), figure_moves (panels in the wrong figure), missing_panels (concrete analyses to RUN), kill_list, and boldest_defensible_fig1. Hands per-figure claims to `figure-composer`. Load when writing or revising a paper.
Also in 5 projects that use this
Norman-burySkillbrainstorming-research
Use before writing any paper - clarifies paper type, discipline, topic, methodology, and chapter structure through natural dialogue
Also in 4 projects that use this
lingzhi227Skilllatex-formatting
Handle LaTeX formatting, templates, and styling for academic papers. Set up conference templates (ICML, ICLR, NeurIPS, AAAI, ACL), fix formatting issues, manage packages, and ensure venue-specific compliance. Use when the user needs to set up a paper template, fix LaTeX formatting, or prepare for submission.
Also in 4 projects that use this
lingzhi227Skillnovelty-assessment
Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision with justification. Use before committing to a research direction.
Also in 4 projects that use this
- +6 more from JimLiu
- +1 more from lingzhi227
Other versions88 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 88
- advaitpaliwal/feynman★ 10ksame name
- companion-inc/feynman★ 10ksame name
- getcompanion-ai/feynman★ 10ksame name
- Norman-bury/research-writing-skill★ 3.4ksame name
- Norman-bury/articlewriting-skill★ 3.4ksame name
- HughYau/AcademicForge★ 2.6ksame name
- K-Dense-AI/claude-scientific-writer★ 2.6ksame name
- xuzhougeng/wisp-science★ 1.1ksame name
- wu-yc/LabClaw★ 1.1ksame name
- LeonChaoX/qinyan-academic-skills★ 910same name
78 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- citation-auditSkill
- claim-evidence-auditSkill
- data-management-planSkill
- manuscript-preflightSkill
- reproducibility-auditSkill
- reviewer-responseSkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 68 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Never invent a paper, DOI, author or year.
- Distinctive: line 27
Search queries and per-source counts.
- Distinctive: line 34
Do not paste a search-result list as if it were a reviewed evidence table.
- Distinctive: line 35
Do not screen at full text before title-abstract inclusion.
- Distinctive: line 36
Do not hide retracted or unreachable records.
“Common” is measured: kept by at least 6 in 10 of the 68 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Literature review
Rules
- A review is a record, not a narrative. Every claim must point at an evidence id.
- Never invent a paper, DOI, author or year. A missing result is
not_found, not a guess. - The search query and each round's per-source counts are part of the record.
Steps
lit_searchwith the question; start with 2–4 sources andmax: 10.lit_sufficiencywith 2–5 subtopics and quotas (minCore,minTotal). Do not proceed whilegaps[]is non-empty unless the user accepts the gap.lit_harvest_runfor the bounded loop when the user wants automation; keepmaxRoundssmall and showrounds[].errors.lit_resolve_oafor the papers the user wants to read; reportMAILTO_REQUIREDinstead of silently skipping.sr_init(orsr_importfor RIS/BibTeX/CSL-JSON) with the identified records.sr_screenat title-abstract, then full-text; conflicts stay open until an adjudicator settles them.research_reportwith sections whose paragraphs cite the surviving claim ids; seal it.
Output
- Search queries and per-source counts.
- Sufficiency report with explicit gaps.
- Screening decisions with reviewer and reason.
- Sealed report path +
dsh-rep-verifyresult.
Never
- Do not paste a search-result list as if it were a reviewed evidence table.
- Do not screen at full text before title-abstract inclusion.
- Do not hide retracted or unreachable records.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

