Academic Paper Summarizer automatically analyzes research papers and generates structured, in-depth summaries using dynamic analysis templates matched to the paper's topic and type. It applies evaluation standards from top-tier conference review criteria (NeurIPS, ICML, ICLR, ACL) to deliver rigorous, comprehensive assessments.
Unlike simple summarization tools, this skill classifies each paper by type — methodology, dataset, multimodal, survey, RL/alignment, and more — then applies a specialized analysis framework tailored to that category.
Key Features
- Dynamic paper classification that identifies paper type (method, dataset, multimodal, tech report, application, survey, RL/alignment, speech/audio, benchmark, analysis) and selects the appropriate evaluation framework
- Conference-level analysis applying standards from NeurIPS, ICML, ICLR, and ACL for rigorous methodology critique and experimental assessment
- Comprehensive output including methodology critique (2000+ characters), experimental assessment, strengths/weaknesses analysis, critical questions, and impact evaluation
- Reproducibility tracking that preserves actual prompts used during analysis in separate text files for transparency and audit
- Structured file output saving summaries as local markdown files organized by research domain
Use Cases
- Batch-process research papers for systematic literature reviews with consistent analysis depth
- Extract key contributions and experimental details from papers in unfamiliar research areas
- Identify dataset usage patterns across studies for meta-analysis or replication planning
- Generate structured paper assessments that feed into larger research reports or grant proposals
How It Works
Users provide paper metadata (title, authors, abstract, topic classification) and research context. The skill classifies the paper type, selects the corresponding evaluation framework, generates a structured analysis following defined quality standards, and saves outputs to organized directories with corresponding prompt files for full reproducibility.
Getting Started
Install the skill — no complex setup or dependencies required. Provide paper metadata and the skill generates a structured analysis. Output files are saved to research/{domain}/ai_summaries/ with prompts preserved separately for audit purposes.
