literature-search
Skill0 starsChanged 11 days agoApache-2.0View on GitHub
Find and read real research papers and back claims with them: sources, studies, evidence, a literature review, checking or completing a reference.
21 other projects use a version of this.
Adopted by
Most recently taken up by
- Light0305/Light-skillstheir own version, first seen Nov 8, 2026
- pradyumnasagar/open-research-skillstheir own version, first seen Nov 8, 2026
- Light0305/Light-Sciencetheir own version, first seen Nov 8, 2026
- ssinder/bioinformatics-agent-skillstheir own version, first seen Nov 1, 2026
- qiaomiaojoe/ai-academic-workflowtheir own version, first seen Oct 27, 2026
- GoogleCloudPlatform/LifeSciencestheir own version, first seen Oct 13, 2026
Used with
Projects with it also use systematic-review.
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.
xjtulycSkillsystematic-review
Use this Skill when conducting a systematic literature review following PRISMA 2020: PICO framework, database search strategy, title/abstract screening, full-text eligibility, data extraction, and GRADE evidence grading.
Also in 3 projects that use this
Other versions21 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 21
- aiming-lab/AutoResearchClaw★ 15ksame name
- wu-yc/LabClaw★ 1.1ksame name
- Light0305/Light-skills★ 886same name
- Light0305/Light-Science★ 885same name
- lingzhi227/agent-research-skills★ 350same name
- jxtse/scientific-research-skills★ 68same name
- ssinder/bioinformatics-agent-skills★ 67same name
- yorkeccak/scientific-skills★ 62same name
- GoogleCloudPlatform/LifeSciences★ 57same name
- xjtulyc/awesome-rosetta-skills★ 34same name
11 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 repository24 other files it gives its agents.
- AGENTS.mdAGENTS.md
- llms.txtllms.txt
- academic-referencesSkill
- annual-accountsSkill
- business-deckSkill
- business-letterSkill
- _checksSkill
- contract-draftingSkill
- diagramSkill
- docxSkill
- e-invoiceSkill
- employment-statementSkill
- html-deckSkill
- meeting-minutesSkill
- paperSkill
- pdfSkill
- powerpointSkill
- requirements-specSkill
- _sharedSkill
- social-posterSkill
- trade-documentsSkill
- whatsapp-exportSkill
- xlsxSkill
- zotero-librarySkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
15 rules. 0 are common, 11 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 15 edited versions we read keep these.
11
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 26
Never cite from memory. A paper is cited only if it came back from a search or lookup in this session, and its details are copied from that …
- Distinctive: line 29
Read before you rely. A title and abstract are enough to list a paper.
- Distinctive: line 32
Never invent an identifier, a DOI, a page number or a quotation.
- Distinctive: line 33
Do the retrieval yourself.
- Distinctive: line 34
If a source is down, say which one and carry on with the others.
- Distinctive: line 57
Every search returns the same fields: source, id, title, abstract, date, authors, venue, doi, citations, url.
- Distinctive: line 105
Keep every result set that came back, even if another call failed.
- Distinctive: line 106
Remove duplicates: same id, then same DOI, then same title.
- Distinctive: line 108
If the first results cover the question, stop and rank 5 to 15 papers by how well they fit the question.
- Distinctive: line 112
Never spend a round rephrasing a search you already ran.
- Distinctive: line 113
Keep only papers that came back from a call in this session.
- Very specific: line 120
When the person needs a comparison, a synthesis or a section of writing, finish the search first, then read the 3 to 5 papers that carry …
- Very specific: line 133
Only if not: does the span contradict it?
- Very specific: line 145
Run verify on every DOI in the reference list.
- Very specific: line 148
Run check on every quotation alongside verify.
“Common” is measured: kept by at least 6 in 10 of the 15 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 search
Adapted from the orx-lit-review skill in alphaXiv OpenResearch (MIT). The
retrieval loop and the citation rules are theirs; the tool, the sources and
the plain-words output are ours. The claim check, its spans and the
reference graph are ported from scholar-mcp by Gonzalo Gorbalan (MIT). Use
academic-references for the reference style and paper to write the paper.
The person asked a question in plain words. They never see a command, an identifier or JSON. Do the search yourself and answer with what the papers say and a short list of sources they can click.
Rules
- Never cite from memory. A paper is cited only if it came back from a search or lookup in this session, and its details are copied from that record. A fabricated citation is worse than no citation.
- Read before you rely. A title and abstract are enough to list a paper. To state what a paper found, read its abstract at least, and its full text when the claim is specific and an open copy exists.
- Never invent an identifier, a DOI, a page number or a quotation.
- Do the retrieval yourself. Do not hand it to a sub-agent.
- If a source is down, say which one and carry on with the others.
The tool
papers.py sits beside this file. It needs no login and no key.
python3 <skill folder>/papers.py search openalex "<query>"
python3 <skill folder>/papers.py search pubmed "<biomedical query>"
python3 <skill folder>/papers.py search arxiv "<query>"
python3 <skill folder>/papers.py paper <DOI | W id | PMID | arXiv id | link>
python3 <skill folder>/papers.py cite apa|ieee|bibtex <id> [<id> ...]
python3 <skill folder>/papers.py verify <DOI> [<DOI> ...]
python3 <skill folder>/papers.py check <id> "<claim>" ["<exact quote>"]
python3 <skill folder>/papers.py refs <id>
python3 <skill folder>/papers.py cited-by <id> [--limit N]openalexcovers journals and conferences in every field, with citation counts. Start here unless the topic is clearly one of the next two.pubmedcovers medicine, health and life science. It accepts PubMed field tags such as[ti]and[mh].arxivcovers preprints in computing, maths, physics and statistics.- Every search returns the same fields: source, id, title, abstract, date, authors, venue, doi, citations, url.
citebuilds the reference from the index record, so names, year, volume and pages are never typed by hand. Check the title's capitals afterwards.citetakes the year from Crossref's print issue when Crossref holds the DOI, since an index's year is often the earlier online-first year.verifyconfirms a DOI exists and returns its registered title and year.checkreturns the sentences a finding can be judged against, each with its field (abstractorfull_text) and exactstart_charandend_char. Full text comes from arXiv's HTML page or Europe PMC when the paper has one; otherwise only the abstract is searched andfull_text_notesays so. With a quote,quote_foundsays whether it is in the text word for word (spaces and curly quotes evened out) and where. It never decides the status; you do, with thejudgequestions it returns.refslists the works a paper cites;cited-bylists the works that cite it, most cited first (25 unless--limitsays otherwise). Both go through OpenAlex. An arXiv id is matched by its exact title (matched_by: title); an empty reference list means OpenAlex has none, not that the paper cites nothing.
Date and ranking controls, the same on every source:
... search openalex "<query>" --after 2020-01-01 --prioritize recency
... search openalex "<query>" --before 2012-01-01 --prioritize historical
... search pubmed "<query>" --limit 20--after and --before are inclusive dates. Do not invent a cut-off just to
favour newer work. --prioritize is default, recency (the person asked
for new or latest), historical (seminal or foundational) or popular
(most cited; only when they ask about influence).
The search loop
Set up
- Build one short query in the person's own words. Do not pad it with general terms and never guess what an acronym stands for.
- Rate how hard the search is from 1 to 10. That sets the number of follow-up rounds: 1 to 3 gets none, 4 to 7 gets one, 8 to 10 gets two.
- Fix one date window and one priority for the whole request. Every later call keeps them.
Run and rank
- Pick the sources that fit. Query two at once when the topic sits between fields. PubMed and arXiv are for their own fields, not a ritual.
- Keep every result set that came back, even if another call failed.
- Remove duplicates: same id, then same DOI, then same title. PubMed and OpenAlex overlap heavily; prefer the record with the DOI and the abstract.
- If the first results cover the question, stop and rank 5 to 15 papers by how well they fit the question. Fewer strong papers beat a padded list.
- Otherwise spend at most the follow-up rounds you set. One round goes after one named gap: a method, a population, a venue, a missing angle. Never spend a round rephrasing a search you already ran.
- Keep only papers that came back from a call in this session.
To widen a search from a paper that fits well, follow its refs for the
work it builds on and cited-by for the work that followed. Each list
counts as a search call: rank and de-duplicate it with the rest.
For "find papers" or "what should I read", return the ranked list and stop.
When the person needs a comparison, a synthesis or a section of writing,
finish the search first, then read the 3 to 5 papers that carry the argument
with paper <id>, and open the open_access_url when the abstract is not
enough.
Writing the answer
- Lead with what the papers say, in plain words, then the sources.
- State each finding with its limits: sample, design, self-reported or measured, correlational or experimental.
- Each finding you state rests on a span from
check, judged in this order:- Does the span support the finding directly, without stretching it?
Fully is
supported; in part ispartial, and say which part holds. - Only if not: does the span contradict it? Yes is
contradicted; otherwiseunsupported. Drop every unsupported and contradicted finding, or say plainly that the paper does not back it. The person never sees the status words.
- Does the span support the finding directly, without stretching it?
Fully is
- Say plainly when the evidence is thin, mixed or missing.
- Quote only text you read, exactly, and cite straight after the quote.
- List sources as full references in the style in use, each with its link:
https://doi.org/<doi>when there is a DOI, otherwise the record'surl. - Tell the person which papers you only saw as abstracts.
Before handing back
Run verify on every DOI in the reference list. Remove or fix any that is
not found, and never keep a reference you could not confirm.
Run check on every quotation alongside verify. A quote with
quote_found: false is fixed from a returned span or taken out.
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.

