paper-presenter

# Paper Presenter Skill ## Purpose Bridge between paper-parser (MinerU output) and beamer-skill. Analyzes parsed paper content + optional source code to produce a structured "materials package" that feeds directly into beamer-skill's `create [topic]` workflow. ## When to Use - After running paper-parser to get structured markdown/figures - User asks to "make a presentation", "create slides", or "summarize this paper as a talk" - User asks to "present the reproduction results" or "make a comparison between paper and code" ## How to Use ### Step 1: Ensure Prerequisites - Parsed output from paper-parser (directory with `full.md`, `images/`, JSON files) - (Optional) Source code from paper-downloader ### Step 2: Run the Preparation Script **Standard paper overview:** ```bash python skills/paper-presenter/prepare_presentation.py workspace/<paper>/parsed/ -o workspace/<paper>/presentation_materials.md ``` **With source code analysis (paper ↔ code comparison):** ```bash python skills/paper-presenter/prepare_presentation.py workspace/<paper>/parsed/ \ --code-dir workspace/<paper>/code/<repo>/ \ --style reproduction-report \ -o workspace/<paper>/presentation_materials.md ``` **Options:** - `--style overview` — Standard paper overview (~15-20 slides) - `--style deep-dive` — Technical deep-dive (~30-40 slides) - `--style reproduction-report` — Paper + code + reproduction results comparison - `--code-dir <dir>` — Source code repo for paper-code alignment analysis - `--paper-info <file>` — paper_info.json for metadata (auto-detected if in standard layout) - `--language en|zh` — Output language ### Step 3: Feed Materials to beamer-skill The output `presentation_materials.md` is designed as **Phase 0 input** for beamer-skill's `create` workflow. Tell the agent: ``` Create a beamer presentation based on the materials in workspace/<paper>/presentation_materials.md ``` The beamer-skill will: 1. Read the materials file (Phase 0) 2. Ask the user about duration, audience, scope (Phase 1) 3. Build a slide structure plan (Phase 2) 4. Draft slides using extracted figures and formulas (Phase 3-4) 5. Run quality checks (Phase 5) ### Key Features for Reproduction Presentations When `--style reproduction-report` and `--code-dir` are used: - **Code-Theory Alignment Table** — maps paper sections to source code files - **Comparison Slide Suggestions** — paper formula on left, code on right - **Implementation Detail Highlights** — what's in code but not in paper - **Delta Analysis Structure** — original results vs reproduced results ## Dependencies - Python 3.10+ - No external libraries required (uses only stdlib + json) - Requires: beamer-skill for the actual presentation generation - **Bundled at**: `../beamer-skill/beamer/` in this monorepo - **Original**: https://github.com/Noi1r/beamer-skill (MIT License by Noi1r) - To install: copy or symlink `beamer-skill/beamer/` to your project's `.gemini/skills/beamer/` ## Output Format The output is a structured Markdown file containing: 1. Paper metadata (title, authors, venue) 2. Section-by-section content analysis 3. Available figures with paths 4. Key mathematical formulas 5. Source code analysis (if provided) 6. Code-theory alignment mapping (if code provided) 7. Suggested slide structure for the chosen style 8. Instructions for beamer-skill agent