Literature Review Evidence Mapper

Heritage and scope

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.

Instructions

1. Classify the review task

Decide what the user needs:

• Narrative/theory review: organize concepts, mechanisms, and debates for an introduction.
• Design precedent review: identify prior treatments, measures, samples, estimands, or analysis strategies.
• Contribution audit: test whether the claimed gap survives contact with the closest prior work.
• Evidence map: summarize what each study establishes, where it applies, and what remains unresolved.
• Systematic-review escalation: when the user needs exhaustive search, screening, risk-of-bias, and PRISMA reporting.

Default to a narrative/evidence-map review unless the user explicitly asks for a systematic review, meta-analysis, or PRISMA-compliant output.

2. Define the question and boundaries

Before summarizing papers, specify:

• Research question or review question.
• Population, setting, outcome, treatment/exposure, and mechanism scope.
• Disciplines and literatures that must be included.
• Time window and language restrictions, if any.
• Inclusion/exclusion logic for sources.
• What counts as "closest prior work."

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.

3. Build the source base

Use the user's supplied sources first. Then identify obvious missing source classes: