paper-analyze
The paper-analyze Claude Code skill fetches academic papers from arXiv, extracts their source files and figures, and generates structured analyses covering the problem statement, motivation, technical methods, experimental results, and key insights. Use this skill when you need comprehensive breakdowns of individual research papers with actual figures extracted from source materials rather than PDFs.
git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7 /tmp/paper-analyze && cp -r /tmp/paper-analyze/skills/paper-analyze ~/.claude/skills/paper-analyzeSKILL.md
# paper-analyze Perform deep analysis of a single academic paper. ## Usage ``` Claude Code: /paper-analyze <arxiv_id or url> Codex: $paper-analyze ``` ## Behavior 1. Fetch paper metadata from arXiv API 2. Attempt to download arXiv source package (.tar.gz) 3. Extract actual figures from source (not screenshots) 4. Read the full paper (PDF if source unavailable) 5. Generate structured analysis ## Figure Extraction Priority order: 1. arXiv source package → extract .png/.jpg/.pdf figures 2. PDF extraction as fallback 3. Name files with arxiv_id prefix to avoid collisions ## Output Format ```markdown # [Paper Title] **arXiv**: [id] | **Authors**: ... | **Year**: ... ## Problem What specific problem does this paper address? ## Motivation Why is this problem important? What gap exists? ## Method Detailed technical approach with key equations/algorithms.  ## Experiments - Datasets, baselines, metrics - Key results table - Ablation findings ## Insights - What can we learn and apply? - Strengths and limitations - Connections to our research ```
Experiment implementation, execution, and monitoring
Literature search and hypothesis formation
Central decision-maker that plans experiments and reflects on results
Report generation and paper writing
Launch an autonomous THINK→EXECUTE→REFLECT experiment loop on a GPU project
Search papers from top AI/ML conferences
Daily arXiv paper recommendations with automatic deduplication
Check status of running autonomous experiment loops