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BytesAgain β€Ί Skills β€Ί Academic Paper Summarizer
πŸ¦€ ClawHub

Academic Paper Summarizer

by @nomorecoding

Academic paper summarization with dynamic SOP selection based on paper topic classification. Supports method, dataset, multimodal, and other paper types with...

Versionv1.0.1
Downloads3,782
Installs26
Stars⭐ 3
#data#research#legal#gaming
TERMINAL
clawhub install paper-summarize-academic

πŸ“– About This Skill

name: paper_summarize description: Academic paper summarization with dynamic SOP selection based on paper topic classification. Supports method, dataset, multimodal, and other paper types with rigorous analysis templates. author: Claude (ε…‹εŠ³εΎ·) version: 1.0.1

Paper Summarize Skill

This skill provides academic-grade paper summarization with dynamic Standard Operating Procedure (SOP) selection based on paper topic classification.

Capabilities

  • Dynamic SOP Selection: Automatically selects appropriate analysis template based on paper type (method, dataset, multimodal, etc.)
  • Rigorous Analysis: Follows top-tier conference review criteria (NeurIPS/ICML/ICLR/ACL)
  • Structured Output: Generates comprehensive summaries with methodology critique, experimental assessment, strengths/weaknesses
  • Local File Storage: Saves summaries to organized directory structure with proper naming
  • Prompt Tracking: Maintains record of actual prompts used for reproducibility
  • Dataset Focus: Explicit attention to training/evaluation datasets used in experiments

    • Supported Paper Types

  • method: Algorithm/architecture papers
  • dataset: Dataset/benchmark papers
  • multimodal: Cross-modal learning papers
  • tech_report: System/model release papers
  • application: Applied AI papers
  • survey: Survey/review papers
  • rl_alignment: RL/Alignment/Safety papers
  • speech_audio: Speech/audio processing papers
  • benchmark: Evaluation/benchmark papers
  • analysis: Empirical analysis papers

    • Usage

    Input Requirements

  • Paper title, authors, abstract
  • Topic classification (one of supported types)
  • Research context (keywords, subtopics)

    • Output Format

  • Local file: {paper_title}.md in research/{domain}/ai_summaries/
  • Content structure:
    • - Paper information (title, authors, venue, links) - Core contribution summary - Methodology critique (2000+ words) - Experimental assessment (1000+ words, with dataset focus) - Strengths and weaknesses - Critical questions for authors - Impact assessment

    Quality Standards

  • Methodology Critique: 2000+ characters, deep technical analysis including pipeline, novelty, mathematical principles, assumptions, prior art comparison, computational cost, and failure modes
  • Experimental Assessment: 1000+ characters, rigorous evaluation with explicit focus on datasets used for training and testing, protocol rigor, baseline fairness, ablation completeness, and statistical significance
  • Overall Analysis: 3000+ characters, critical perspective
  • Technical Precision: Correct terminology, specific method names, exact metrics

    • Workflow Integration

    This skill integrates with the broader research workflow:

    1. Paper Discovery: Works with arXiv search results 2. Quality Filtering: Processes papers that pass relevance screening 3. Batch Processing: Can be called repeatedly for multiple papers 4. Report Generation: Outputs feed into final research report

    Configuration

    SOP templates are defined in:

  • src/lib/agents/topic-sops.ts (primary location)
  • summarization_prompt.ts (backup/reference)

    • Both files contain identical SOP definitions with shared output format requirements.

    Examples

    # Summarize a method paper
paper_summarize --title "SongEcho: Cover Song Generation" --topic "method" --abstract "..." --authors "..."
    Summarize a dataset paper  
    
paper_summarize --title "MusicSem: Language-Audio Dataset" --topic "dataset" --abstract "..." --authors "..."

    Files Created

  • research/{domain}/ai_summaries/{paper_title}.md
  • research/{domain}/prompts/{paper_title}_prompt.txt
  • Directory structure automatically created if missing

    • πŸ’‘ Examples

    # Summarize a method paper
paper_summarize --title "SongEcho: Cover Song Generation" --topic "method" --abstract "..." --authors "..."
    Summarize a dataset paper  
    
paper_summarize --title "MusicSem: Language-Audio Dataset" --topic "dataset" --abstract "..." --authors "..."

    βš™οΈ Configuration

    SOP templates are defined in:

  • src/lib/agents/topic-sops.ts (primary location)
  • summarization_prompt.ts (backup/reference)

    • Both files contain identical SOP definitions with shared output format requirements.