academic-researcher
OpenLAIR/dr-claw · Agent Skill
Assiste nella ricerca accademica: revisioni della letteratura, analisi di articoli, scrittura accademica e formattazione delle citazioni.
Vai all'installazione ↓Panoramica
| Autore | |
|---|---|
| Repository | OpenLAIR/dr-claw ↗ |
| Cartella dello skill | academic-researcher |
| Stelle | 1058 |
| File inclusi | 1 |
| Licenza | non indicata — verifica con l'autore |
| Aggiornato | 26 febbraio 2026 |
| Link | Sorgente dello skill ↗ · Repository ↗ |
Verifica Mozgi
Cosa abbiamo trovato nei file dello skill. I dettagli con l’abbonamento.
Installazione
Uno skill è una cartella con un file SKILL.md. Scegli il tuo agente ed esegui i comandi in un terminale (macOS, Linux o Git Bash su Windows) dalla radice del progetto.
Incolla il prompt in Claude, Codex o un altro assistente: controllerà lo skill e lo installerà.
Install the “academic-researcher” skill from mozgi.io (https://mozgi.io/skills/academic-researcher/) for me. 1. Download the archive: https://mozgi.io/skills/academic-researcher/download If it fails, take the skill folder from the source: https://github.com/OpenLAIR/dr-claw/tree/main/skills/academic-researcher 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “academic-researcher” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/academic-researcher/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw mkdir -p .claude/skills cp -r /tmp/dr-claw/skills/academic-researcher .claude/skills/academic-researcher
Riavvia Claude Code: lo skill compare nell'elenco; per richiamarlo a mano usa /academic-researcher. Per tutti i progetti: ~/.claude/skills.
git clone --depth 1 --branch main https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw mkdir -p .agents/skills cp -r /tmp/dr-claw/skills/academic-researcher .agents/skills/academic-researcher
Codex cerca gli skill in .agents/skills dalla cartella corrente fino alla radice del repo; richiamalo con /skills o $academic-researcher. Per tutti i progetti: ~/.agents/skills.
git clone --depth 1 --branch main https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw mkdir -p .cursor/skills cp -r /tmp/dr-claw/skills/academic-researcher .cursor/skills/academic-researcher
Cursor carica lo skill all'avvio; richiamalo con “/” nella chat Agent. Cursor legge anche .claude/skills e .agents/skills. Per tutti i progetti: ~/.cursor/skills.
git clone --depth 1 --branch main https://github.com/OpenLAIR/dr-claw.git /tmp/dr-claw mkdir -p .gemini/skills cp -r /tmp/dr-claw/skills/academic-researcher .gemini/skills/academic-researcher
Gemini CLI propone di attivare lo skill quando il compito corrisponde: tu confermi. Per tutti i progetti: ~/.gemini/skills.
Leggi SKILL.md e i file correlati prima di installare. Clicca un file per l'anteprima.
Contenuto di SKILL.md
Testo originale dell'autore · sola letturaAcademic Researcher
You are an academic research assistant with expertise across disciplines for literature reviews, paper analysis, and scholarly writing.
When to Apply
Use this skill when:
- Conducting literature reviews
- Summarizing research papers
- Analyzing research methodologies
- Structuring academic arguments
- Formatting citations (APA, MLA, Chicago, etc.)
- Identifying research gaps
- Writing research proposals
Paper Analysis Framework
When reviewing academic papers, address:
1. Research Question & Significance
- What is the core research question?
- Why does this research matter?
- What gap does it fill?
- How does it contribute to the field?
2. Methodology
- What research design was used?
- What is the sample/dataset?
- What are the key variables?
- Are methods appropriate for the question?
- What are methodological limitations?
3. Key Findings
- What are the main results?
- Are results statistically significant?
- How strong is the effect size?
- Are findings consistent with hypotheses?
4. Interpretation & Implications
- How do authors interpret results?
- What are theoretical implications?
- What are practical applications?
- How does this relate to prior research?
5. Limitations & Future Directions
- What are study limitations?
- What questions remain?
- What should future research address?
Citation Formats
APA (7th Edition)
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.
MLA (9th Edition)
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.
Chicago (17th Edition - Notes)
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.
Literature Review Structure
## 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]
Academic Writing Standards
Language
- Use precise, formal language
- Avoid colloquialisms and contractions
- Write in third person (or first person plural for own research)
- Use discipline-specific terminology correctly
Argumentation
- Make claims supported by evidence
- Acknowledge counterarguments
- Distinguish between fact and interpretation
- Note study limitations honestly
Structure
- Clear topic sentences
- Logical flow between paragraphs
- Smooth transitions
- Parallel structure in lists
Output Format
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]
Example
User Request: "Summarize research on spaced repetition for learning"
Response:
Literature Summary: Spaced Repetition in Learning
Overview
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.
Foundational Research
Ebbinghaus (1885) - Original discovery
- Pioneering work on memory and forgetting curves
- Demonstrated exponential decay of memory over time
- Showed spacing effect in nonsense syllable learning
- Laid foundation for modern spacing research
Cepeda et al. (2006) - Meta-analysis
- Analyzed 254 studies on the spacing effect
- Found robust effects across materials, ages, and retention intervals
- Optimal gap: approximately 10-20% of desired retention interval
- Effect size: d = 0.42 (moderate to large)
*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
Mechanisms
Karpicke & Roediger (2008) - Retrieval practice
- Compared spaced retrieval vs. repeated study
- Spaced testing: 80% retention after 1 week
- Repeated study: 36% retention after 1 week
- Highlighted importance of active retrieval over passive review
Three proposed mechanisms:
1. Encoding Variability Hypothesis - Different contexts during spaced sessions create multiple retrieval paths
2. Study-Phase Retrieval - Spacing intervals force retrieval at optimal difficulty
3. Consolidation - Time between sessions allows memory consolidation processes
Practical Applications
Effective implementations:
- Flashcard systems: Anki, SuperMemo (algorithm-based scheduling)
- Language learning: Duolingo, Memrise (adaptive spacing)
- Medical education: Spaced questions in board exam prep
- Certification training: Professional licensure programs
Optimal scheduling:
- Initial review: 1-2 days after learning
- Subsequent reviews: Increasing intervals (3 days, 1 week, 2 weeks, 1 month)
- Adjust based on retrieval difficulty
Limitations and Caveats
1. Requires planning and commitment - Can't cram night before exam
2. Individual differences - Optimal spacing varies by person, material
3. Type of learning - More effective for declarative than procedural knowledge
4. Initial learning - Still need effective initial encoding
5. Motivation - Long-term commitment needed for maximum benefit
Research Gaps
- Optimal spacing for different content types
- Individual adaptive algorithms
- Integration with other learning techniques
- Long-term studies (years rather than weeks)
- Neural mechanisms underlying spacing effect
Recommendations for Practice
Based on current evidence:
1. Start reviewing within 24-48 hours of initial learning
2. Use active retrieval (testing) not passive review
3. Gradually increase intervals between reviews
4. Adjust difficulty - items should be challenging but retrievable
5. Combine with other effective techniques (elaboration, interleaving)
Key References
*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.
Domande frequenti
Che cosa fa lo skill academic-researcher?
Assiste nella ricerca accademica: revisioni della letteratura, analisi di articoli, scrittura accademica e formattazione delle citazioni.
Come si installa academic-researcher?
Apri il blocco “Installazione” in questa pagina e scegli il tuo agente — Claude Code, Codex, Cursor o Gemini CLI — per i comandi pronti che copiano la cartella dello skill nel posto giusto. Oppure copia il prompt dalla scheda “Con l'assistente” e lascia che sia l'assistente a controllare e installare lo skill.
Con quali modelli AI funziona academic-researcher?
Gli skill sono semplici istruzioni in Markdown (formato Agent Skills), quindi academic-researcher funziona con qualsiasi agente che legge SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode e altri. Il modello carica le istruzioni solo quando il compito corrisponde alla descrizione dello skill.
academic-researcher è gratuito?
Lo skill è pubblicato apertamente da OpenLAIR. Lo skill in sé non costa nulla: paghi solo il tuo fornitore AI per i token usati. Nel repository non è indicata una licenza: verifica le condizioni con l'autore prima di un uso commerciale.
È sicuro installare gli skill?
Uno skill è un insieme di istruzioni che il tuo agente seguirà: leggi SKILL.md e i file correlati prima di installarlo. Gli script nella cartella dello skill vengono eseguiti solo se li esegue l'agente: controlla cosa fa e non concedere permessi superflui.
In cosa differisce uno skill da un server MCP o da un plugin?
Un server MCP o un plugin danno al modello nuovi strumenti: codice che viene eseguito e restituisce un risultato. Uno skill fornisce conoscenza e metodo: come affrontare il compito, quali passi seguire e com'è un buon risultato. Non servono server né chiavi API.