Perform systematic academic literature research, extract structured data, and synthesize findings for a specific research need.
Install
npx skillscat add akwancakra/nids-cnn-lstm-autoencoder Install via the SkillsCat registry.
When to use
Use this skill when the user asks for academic research, literature review, systematic search, paper comparison, or synthesis of findings.
Core capabilities
Systematic literature search
- Build keywords and boolean strings
- Search scholarly sources (Scholar, IEEE Xplore, ScienceDirect, PubMed, ACM)
- Define inclusion/exclusion criteria
- Backward and forward citation chasing
- Log search strategy for reproducibility
Source evaluation
- Check relevance to research question
- Assess methodological quality
- Verify venue and author credibility
- Identify bias and limitations
- Prioritize by impact and recency
Structured data extraction (per paper)
- Summary
- Methodology
- Results
- Key findings
- Limitations
- Important concepts
- Contributions
- Implications
- Further readings
Synthesis and analysis
- Find patterns and trends
- Identify gaps and contradictions
- Cluster by themes
- Compare methods and outcomes
- Propose hypotheses or future directions
Documentation and reporting
- Produce structured literature review
- Build comparison tables
- Format citations (APA/IEEE/Harvard)
- Create annotated bibliography
- Provide simple visuals or PRISMA flow
Workflow
Stage 1: Clarify research needs
Input: topic, research questions, goals
Output: research protocol (keywords, scope, criteria)
Stage 2: Systematic search
Input: research protocol
Output: candidate list with metadata
Stage 3: Screening and selection
Input: candidates
Output: final corpus with selection notes
Stage 4: Data extraction
Input: final corpus
Output: structured extraction table (CSV/Excel)
Stage 5: Synthesis and writing
Input: extraction table
Output: literature review draft with citations
Quality criteria
- Relevance: direct alignment with research questions
- Credibility: peer-reviewed preferred
- Recency: last 5 years unless seminal
- Traceability: clear link from source to claim
Output templates
Search report (markdown)
## Search Strategy
Database: Google Scholar
Query: ("cnn-lstm" OR "autoencoder") AND ("intrusion detection" OR "nids")
Date: 2026-02-02
Results: 847 hits
After filter: 234 hitsExtraction table (columns)
Author | Year | Methodology | Sample | Key Findings | Limitations
Synthesis structure (markdown)
## Theme 1: [Name]
[Synthesis with citations]
## Theme 2: [Name]
[Synthesis with citations]
## Research Gaps
[Specific gaps]Limitations
- Cannot access paywalled sources without credentials
- Methodology appraisal still needs human validation
Usage example
research_topic: "Zero-day detection in NIDS using autoencoders"
research_questions:
- "How effective are hybrid CNN-LSTM autoencoders for zero-day detection?"
- "What datasets and metrics are used for cross-dataset validation?"
inclusion_criteria:
- "Empirical studies with quantitative results"
- "2019-2026"
exclusion_criteria:
- "Non-technical reviews"
databases:
- "Google Scholar"
- "IEEE Xplore"
max_papers: 30
citation_style: "APA 7th"