skills/54-scdenney-open-science-skills/skills/literature-review/SKILL.md
Build or audit a literature review: evidence map, gaps, synthesis plan.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research literature-reviewInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This is an original Open Science Skills workflow for experimental and computational social science. It remixes high-level ideas from Cheng-I Wu's Academic Research Skills for Claude Code (CC BY-NC 4.0), especially evidence mapping, source verification, and mode separation between narrative literature review and formal systematic review. It is not a full ARS pipeline and should not copy ARS prose.
Decide what the user needs:
Default to a narrative/evidence-map review unless the user explicitly asks for a systematic review, meta-analysis, or PRISMA-compliant output.
Before summarizing papers, specify:
If the user only gives a broad topic, first produce a short scoping memo with 2-4 possible review boundaries rather than writing a generic review.
Use the user's supplied sources first. Then identify obvious missing source classes:
Run citation-check when the source list is large, messy, DOI-heavy, or likely to contain stale working papers.
For each important source, record:
Do not produce chronological "Author A says X, Author B says Y" prose unless chronology is theoretically important.
Organize sources into 3-6 clusters. Prefer conceptual or mechanism clusters over method-only clusters:
For each cluster, state what is settled, what is contested, and what would change the interpretation.
Write a gap verdict:
When the gap is weak, propose a better contribution frame rather than only criticizing it.
narrative-building after the evidence map exists to turn the review into the "Why-to-If-Then" funnel.hypothesis-building when the review implies falsifiable expectations and estimands.pre-registration-writing when the review supports confirmatory hypotheses.methods-reporting when reviewing how prior studies report designs, sample flow, and transparency.journal-review when auditing someone else's manuscript for novelty and placement.Produce a Literature Review Evidence Map:
# Literature Review Evidence Map
Review question:
Scope and exclusions:
Search/source base:
Gap verdict: Holds / Partly holds / Does not hold / Cannot assess
## Closest Prior Work
| Source | What it actually establishes | Boundary | Relation to user's claim |
## Evidence Clusters
### Cluster 1: <name>
Settled:
Contested:
Missing:
Key sources:
## Contribution Diagnosis
Claimed gap:
Verdict:
Better contribution frame:
## Literature Review Architecture
1. <section purpose>
2. <section purpose>
3. <section purpose>
## Sentences the Review Must Earn
- <sentence-level claim that needs source support>
## Sources Needing Verification
| Source | Why |
citation-check was invoked or recommended when source integrity was uncertain.narrative-building.tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.