Builds or audits a literature review: evidence map, closest prior work, gap verdict, and synthesis plan. Use to check whether a contribution is novel, map what a literature establishes, or organize a review; systematic reviews get a protocol scaffold.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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 the separation between narrative literature review and formal systematic review. It is not a full ARS pipeline.
## Instructions
### 1. Classify the review task
Decide which of these 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.
…
The line at the top of this page pins the label git:20261008.697c89f, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (6588 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag
Source
GitHub
scdenney/open-science-skills · 69 stars · license a license file GitHub does not identify · pushed 2026-11-05 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_yvza7g2z5gjskncr
GET https://markdownregistry.com/api/v1/resolve?ref=scdenney/open-science-skills/literature-review
GET https://markdownregistry.com/api/v1/blob/7056d38acddaea4f30c2b646a8a1bdd42848b483071798cf64b8b0558896fa72
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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incarnamind/incarnamind · resources/skills/literature-review/SKILL.md · Writes a literature review across the User's Documents on the Question's topic, synthesised by theme rather than one…