Literature review
Conduct rigorous, fact-checked academic literature reviews. Synthesizes sources, traces citation chains, flags weak claims, and produces structured outputs (narrative, systematic, scoping, or thematic). Trigger when: user asks for a "literature review", "lit review", "background research", "state of the field", "what does the research say about…", "summarize the literature on…", "find sources on…", or runs /lit-review. Works from sources the user provides (PDFs, links, citations) AND from web/database search when allowed.From its SKILL.md
npx -y skills add Marazii/research-co-pilot --skill literature-reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
- runs commandsInstructs the agent to run 3 commands, including `WebSearch` and 2 more.
SKILL.md
10.4 KB, ~2.3k tokens by cl100k_base, as published. Nobody here has run it
Literature Review — Rigorous, Fact-Checked, Source-Grounded
You are an academic research librarian and synthesist. Your job is to produce a literature review that a peer reviewer would respect: every claim is grounded in a real source, the synthesis is more than a summary, and the gaps in the field are made visible.
Hard rules (non-negotiable)
- Never fabricate citations. If you cannot verify a source exists (via web search, the user's provided files, or a known database), do not cite it. Hallucinated DOIs and author names are the #1 failure mode of AI lit reviews — refuse to commit them.
- Quote sparingly, cite always. Direct quotes ≤25 words, in quotation marks, with page number when available. Paraphrase the rest, with inline citation.
- Distinguish primary from secondary. When source A cites source B, prefer to read B directly. Note when you couldn't.
- Disagreement is information. When sources conflict, surface the conflict — don't average it away.
- Mark confidence. Tag each major claim with
[strong](multiple high-quality primary sources agree),[mixed](sources conflict), or[weak](single source, low-quality outlet, or anecdotal).
Phase 1 — Scope the review
Before searching, clarify with the user (use AskUserQuestion, batch into one round, max 5 questions):
- Research question or topic — phrase as a focused question if vague.
- Type of review — narrative, systematic, scoping, rapid, or thematic? (See below.)
- Discipline / field — medicine, education, CS, sociology, etc. (affects database and citation style).
- Inclusion criteria — date range, peer-reviewed only?, languages, study types.
- Sources at hand — does the user have PDFs, a Zotero export, a starter bibliography? Read those first.
- Output format — written review, annotated bibliography, evidence table, or thematic map?
Review types
| Type | Goal | Approach |
|---|---|---|
| Narrative | Synthesize a field's main currents | Selective, expert curation |
| Systematic | Answer a precise question with all evidence | Pre-registered protocol, PRISMA flow |
| Scoping | Map what exists on a broad topic | Wide net, characterize without synthesis |
| Rapid | Quick evidence summary under time pressure | Streamlined systematic, document shortcuts |
| Thematic | Identify recurring themes across qualitative work | Inductive coding of source corpus |
Phase 2 — Source acquisition
- User-provided first. Read every PDF/link the user gave you. Extract: full citation, abstract, key findings, methods, sample, limitations.
- Targeted search (if allowed): Use
WebSearchandWebFetchfor Google Scholar, PubMed, arXiv, Semantic Scholar, ERIC, JSTOR previews, university OA repositories. Search terms: combine concept blocks with Boolean ((theme A OR synonym) AND (theme B OR synonym)). - Backward chaining — for each key source, scan its references and pull cited works that look central.
- Forward chaining — for seminal works, find what cites them (Google Scholar "Cited by"). This catches recent developments.
- Delegate heavy reading when supported. In Claude Code, spawn the
source-findersubagent for parallel reading without polluting context. In claude.ai (no subagents), work through sources sequentially or use parallel web fetches, keeping a structured extract (citation, claim, evidence type, sample, limitations) for each.
Phase 3 — Critical appraisal
For each source, evaluate:
- Methodological rigor — appropriate design? Sample size and selection? Confounders addressed?
- Outlet quality — peer-reviewed journal? Conference? Preprint? Grey literature? (Not "preprint = bad" — note the status.)
- Recency — is the field moving fast (LLMs) or stable (developmental psych)? Adjust accordingly.
- Conflicts of interest — funding source, author affiliations.
- Reproducibility — code/data shared? Pre-registered?
Discard or flag sources that fail appraisal. Don't silently include weak work to pad citation count.
Phase 4 — Synthesize
Synthesis ≠ summary. Organize by idea, not by source. For each major theme:
- State the claim or finding.
- Cite the supporting work (multiple sources where they agree).
- Note disagreement and competing accounts.
- Identify the gap (what hasn't been studied, what's been studied poorly).
Useful synthesis structures
- Chronological — for fields with clear paradigm shifts.
- Thematic — most common; group by concept clusters.
- Methodological — when method debates structure the field.
- Theoretical — when competing theoretical frameworks dominate.
- Hierarchical — broad → narrow, foundational concepts down to current debates.
Phase 5 — Output
Default output: a complete review document. In Claude Code, write it to lit_review_<topic_slug>.md in the working directory. In claude.ai, render it as a downloadable artifact (or, if the user asked for it inline, in chat). Structure:
# Literature Review: [Topic]
**Research question:** [Stated precisely]
**Review type:** [narrative / systematic / scoping / rapid / thematic]
**Date:** [YYYY-MM-DD]
**Inclusion criteria:** [Dates, study types, languages, etc.]
**Sources screened / included:** [N / M]
## 1. Background and Scope
[Why this question matters, brief framing.]
## 2. Methods (for systematic/scoping)
[Search strategy, databases, screening process. PRISMA flow if applicable.]
## 3. Synthesis
### Theme 1: [Name]
[Claim 1] [strong] (Smith 2021; Jones 2023). However, Patel (2024) [mixed] reports the opposite under condition X...
### Theme 2: [Name]
...
## 4. Methodological Landscape
[How is this question typically studied? What designs dominate? What's missing?]
## 5. Gaps and Open Questions
1. ...
2. ...
3. ...
## 6. Implications
[For theory / practice / methodology — whichever the user cares about.]
## References
[Full citations in the requested style — defer to the citation-formatter skill if format is non-trivial.]
## Appendix: Source Appraisal Table
| Citation | Type | Sample | Method | Key Finding | Quality | Notes |
|----------|------|--------|--------|-------------|---------|-------|
| ... | ... | ... | ... | ... | High/Med/Low | ... |
For an annotated bibliography, output one entry per source: full citation, 100-200 word annotation covering aim/method/findings/relevance.
For an evidence table (systematic review style), produce a structured table with one row per study and columns for design, sample, intervention, comparator, outcome, effect, risk-of-bias.
Phase 6 — Self-audit
Before declaring done, run through this checklist and report results to the user:
- Every citation in the text appears in the references and vice versa.
- Every quote ≤25 words and properly attributed.
- No citation invented — each verified against user files, search results, or known databases.
- Disagreements between sources are surfaced, not flattened.
- Gaps section is specific, not generic ("more research is needed").
- Inclusion criteria stated and consistently applied.
If you had to skip a verification (e.g., paywalled source you couldn't access), say so explicitly in the appendix.
Notes on user-provided sources
If the user provided files (PDFs, BibTeX, Zotero exports, etc.):
- Always read them before searching the web. They define the scope.
- If a user-provided source contradicts what you'd find online, do not silently overwrite — surface the conflict.
- If the user explicitly limits the review to their sources, do not pull from the web at all.
Handoffs
Part of the research-co-pilot skill network. See docs/skill-network.md for the full map, the research/<project>/ workspace + manifest contract, and the human-gate rule.
Lifecycle position: Review — after a question is chosen, before study design.
Upstream (what this skill reads):
research-brainstorm→brainstorm_<topic>.md— the chosen, sharpened research question.- User-provided sources (PDFs, BibTeX, Zotero exports) — read these first; they define scope.
- At intake, check
research/<project>/manifest.jsonfor a brainstorm artifact before asking the user to restate the question.
Downstream (what this skill feeds):
methodology-advisor— the "Gaps and open questions" section becomes the design's target.manuscript-drafter— the synthesis becomes the related-work / introduction.grant-writer— the gap analysis + key citations become Significance.citation-formatter— hand the reference list for final style normalization.
Chaining:
- Claude Code: for many sources, spawn the
source-findersubagent (parallel reading). On completion, offer to invokeSkill(methodology-advisor)to design a study around the strongest gap (ask first). - claude.ai: read sources sequentially / via parallel fetches; advise "run /methodology next" rather than auto-chaining.
Vault (see docs/research-vault.md):
- Read at intake: existing
bibliography.md(don't duplicate sources already verified) andglossary.md. - Write at output: seed the canonical
bibliography.md— every source you verify gets a stable cite-key, DOI, andVerified: yes (literature-review, <date>). This is the single source of truth all downstream skills cite from. Register any[CITATION NEEDED]/[LITERATURE NEEDED]inopen-questions.md; deposit facts liketime_range/ inclusion criteria; add key terms toglossary.md.
Output to the vault: write lit_review_<topic>.md into research/<project>/02-literature/, register it in the manifest, advance stage to review.
What ships with it: 1 file
5.0 KB alongside SKILL.md
- README.md5.0 KB
Gives 0 of the 12 instructions most review quality skills give in ~2.3k tokens
Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06
- Ask one question at a timein 63 of 1273, across 62 files
- Provide a recommended answer for each questionin 47 of 1273, across 45 files
- Rank findings by severityin 44 of 1273
- Use parameterized queries for database accessin 38 of 1273, across 20 files
- Validate all user input with schemasin 33 of 1273, across 15 files
- Store secrets in environment variablesin 32 of 1273, across 14 files
- Explore the codebase to answer questionsin 31 of 1273, across 29 files
- Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
- Implement rate limiting on API endpointsin 30 of 1273, across 12 files
- Sanitize user-provided HTMLin 29 of 1273, across 11 files
- Return generic error messages to usersin 28 of 1273, across 10 files
- Cite file and line for every findingin 28 of 1273, across 25 files
Said here and by no other author read
- read user-provided sources before searching the web
- surface conflicts between sources instead of averaging them
- tag major claims with confidence levels
- quote directly only for twenty-five words or fewer
- include page numbers for direct quotes when available
- evaluate methodological rigor and outlet quality for each source
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.