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
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".