How do I install the Recipe Academic Literature Review skill?

Run npx skillmds@latest add flowleap-ai/recipe-academic-literature-review in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Recipe Academic Literature Review safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Recipe Academic Literature Review?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Recipe Academic Literature Review free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Recipe Academic Literature Review?

flowleap-ai (@flowleap-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Recipe Academic Literature Review by flowleap-ai

Name: Recipe Academic Literature Review
Author: flowleap-ai

Recipe Academic Literature Review

Map the gap between published research and filed patents — a scholarly sweep across Semantic Scholar, arXiv, and OpenAlex aligned against a matching patent search, output centered on the published-versus-protected gap rather than a ranked novelty list. Trigger when the user asks for a literature review, a state-of-the-art survey, or a comparison of academic research against patents.

flowleap-ai Updated Sep 17, 2026

File contents

Recipe: Academic Literature Review

Combine academic and patent searches to map what a field has published against what it has protected.

Prefer academic (Semantic Scholar + arXiv) for CS/ML papers and preprints; prefer npl (OpenAlex) for broad cross-disciplinary journal coverage and open-access filtering.

Steps

Step 1: Academic Search

flowleap --json academic search "<research topic>" --limit 20
flowleap --json academic search "<research topic>" --source arxiv --from-year 2020

Step 2: Widen to OpenAlex NPL

flowleap --json npl "<research topic>" --from-year 2020 --limit 10

Step 3: Patent Search for the Same Topic

Write the CQL yourself from the topic's discriminating terms (the specific subject matter, not the field name — method in flowleap-patent), probe the count, then search:

flowleap --json tools run search_patents query='<self-written CQL>' range=1-1 details=false
flowleap --json patent search --query "<self-written CQL>" --limit 20

Step 4: Synthesize the Gap

Align the academic themes against the patent CPC and assignee clusters. Flag topics heavily published but lightly patented (open R&D space) and topics heavily patented but lightly published (crowded IP). Done when each major theme is classified on the published-versus-protected axis.

Visual deliverable

To hand off Step 4's published-versus-protected map as a shareable artifact, follow this recipe's analysis through to the end, then render it with recipe-custom-dashboard — the filing-trends template (multi-series comparison over time) is the closest fit, adapted to plot academic output against patent filings per theme rather than per applicant. Analysis logic stays here; the dashboard skill only owns presentation.

Output

Academic papers (title, authors, year, source, citation counts)
Related patents (publication number, title, applicant, date, CPC)
A published-versus-protected map: themes tagged as open R&D space or crowded IP

---name: recipe-academic-literature-reviewdescription: Map the gap between published research and filed patents — a scholarly sweep across Semantic Scholar, arXiv, and OpenAlex aligned against a matching patent search, output centered on the published-versus-protected gap rather than a ranked novelty list. Trigger when the user asks for a literature review, a state-of-the-art survey, or a comparison of academic research against patents.---# Recipe: Academic Literature ReviewCombine academic and patent searches to map what a field has published againstwhat it has protected.Prefer `academic` (Semantic Scholar + arXiv) for CS/ML papers and preprints;prefer `npl` (OpenAlex) for broad cross-disciplinary journal coverage andopen-access filtering.## Steps### Step 1: Academic Search```bashflowleap --json academic search "<research topic>" --limit 20flowleap --json academic search "<research topic>" --source arxiv --from-year 2020```### Step 2: Widen to OpenAlex NPL```bashflowleap --json npl "<research topic>" --from-year 2020 --limit 10```### Step 3: Patent Search for the Same TopicWrite the CQL yourself from the topic's discriminating terms (the specificsubject matter, not the field name — method in `flowleap-patent`), probe thecount, then search:```bashflowleap --json tools run search_patents query='<self-written CQL>' range=1-1 details=falseflowleap --json patent search --query "<self-written CQL>" --limit 20```### Step 4: Synthesize the GapAlign the academic themes against the patent CPC and assignee clusters. Flagtopics heavily published but lightly patented (open R&D space) and topicsheavily patented but lightly published (crowded IP). Done when each major themeis classified on the published-versus-protected axis.## Visual deliverableTo hand off Step 4's published-versus-protected map as a shareable artifact,follow this recipe's analysis through to the end, then render it with`recipe-custom-dashboard` — the **filing-trends** template (multi-seriescomparison over time) is the closest fit, adapted to plot academic outputagainst patent filings per theme rather than per applicant. Analysis logicstays here; the dashboard skill only owns presentation.## Output- Academic papers (title, authors, year, source, citation counts)- Related patents (publication number, title, applicant, date, CPC)- A published-versus-protected map: themes tagged as open R&D space or crowded IP

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