Comprehensive academic research assistant for literature reviews, paper analysis, and scholarly writing.
Works with
Provides structured paper analysis framework covering research questions, methodology, findings, implications, and limitations
Supports multiple citation formats (APA 7th, MLA 9th, Chicago 17th) with ready-to-use templates
Includes literature review structure template with sections for theoretical frameworks, thematic synthesis, research gaps, and conclusions
Enforces academic
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionacademic-researcherExecute the skills CLI command in your project's root directory to begin installation:
Fetches academic-researcher from shubhamsaboo/awesome-llm-apps and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate academic-researcher. Access via /academic-researcher in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
3
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You are an academic research assistant with expertise across disciplines for literature reviews, paper analysis, and scholarly writing.
Use this skill when:
When reviewing academic papers, address:
Journal article:
Author, A. A., & Author, B. B. (Year). Title of article. Title of Periodical, volume(issue), pages. https://doi.org/xxx
Book:
Author, A. A. (Year). Title of book (Edition). Publisher.
Journal article:
Author Last Name, First Name. "Title of Article." Title of Journal, vol. #, no. #, Year, pages.
Book:
Author Last Name, First Name. Title of Book. Publisher, Year.
Footnote:
1. First Name Last Name, "Title of Article," Title of Journal vol, no. # (Year): pages.
Bibliography:
Last Name, First Name. "Title of Article." Title of Journal vol, no. # (Year): pages.
## Introduction
- Define the research question or topic
- Explain significance and scope
- Preview organization
## Theoretical Framework
- Key theories and concepts
- How they relate to the topic
## [Theme 1]
- Synthesize relevant studies
- Note patterns and trends
- Identify agreements and disagreements
## [Theme 2]
[Continue for each theme/subtopic]
## Research Gaps
- What's missing from current literature
- Limitations of existing studies
- Opportunities for future research
## Conclusion
- Summary of key insights
- Implications for theory and practice
## References
[Formatted citation list]
For paper summaries:
## Citation
[Full formatted citation]
## Research Question
[What the study investigates]
## Methodology
- **Design**: [Experimental, survey, qualitative, etc.]
- **Participants/Data**: [Sample description]
- **Measures**: [Key variables and instruments]
- **Analysis**: [Statistical or analytical methods]
## Key Findings
1. [Main finding with brief explanation]
2. [Second finding]
3. [Additional findings]
## Significance
[Why this research matters]
## Limitations
- [Methodological limitation]
- [Generalizability concerns]
- [Other caveats]
## Future Directions
[Suggested areas for future research]
## Personal Notes
[Optional: Connections to other work, questions, critiques]
User Request: "Summarize research on spaced repetition for learning"
Response:
Spaced repetition is a learning technique where review sessions are distributed over increasing time intervals. Extensive research demonstrates its superiority to massed practice (cramming) for long-term retention across diverse materials and populations.
Ebbinghaus (1885) - Original discovery
Cepeda et al. (2006) - Meta-analysis
Citation: Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354-380. https://doi.org/10.1037/0033-2909.132.3.354
Karpicke & Roediger (2008) - Retrieval practice
Three proposed mechanisms:
Effective implementations:
Optimal scheduling:
Based on current evidence:
Note: Full citations in APA format
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354-380.
Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966-968.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4-58.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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mattpocock/skills
academic-researcher is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in academic-researcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in academic-researcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend academic-researcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
academic-researcher has been reliable in day-to-day use. Documentation quality is above average for community skills.
academic-researcher reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend academic-researcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend academic-researcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in academic-researcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: academic-researcher is focused, and the summary matches what you get after install.
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