一键导入
page-gen
Generate an academic paper project webpage from PDF using parse_paper, match_template, render_html, review_html_visual, and extract_table_html.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Generate an academic paper project webpage from PDF using parse_paper, match_template, render_html, review_html_visual, and extract_table_html.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | page-gen |
| description | Generate an academic paper project webpage from PDF using parse_paper, match_template, render_html, review_html_visual, and extract_table_html. |
| metadata | {"clawphd":{"emoji":"🌐","requires":{}}} |
Turn a paper PDF into a polished HTML project page with iterative visual refinement.
| Tool | Purpose |
|---|---|
parse_paper | Parse PDF into markdown (pymupdf4llm) + extract complete figures with captions as screenshots |
match_template | Rank page templates by style preferences (reads tags.json) |
render_html | Render local HTML into PNG screenshot (Playwright) |
review_html_visual | Vision-based review of rendered screenshot |
extract_table_html | Convert table image to semantic HTML table |
Call parse_paper with the user PDF path.
markdown_path and a figures array.num (Figure number), caption (full caption text from the paper), and path (high-res screenshot of the complete figure region).From parsed markdown:
titleauthorsaffiliationCall match_template with the user's style preferences (or defaults).
The tool returns ranked template candidates with paths. You MUST use these templates.
CRITICAL: Do NOT write HTML/CSS from scratch. You MUST base your page on the selected template.
index.html using read_file to understand its full structure.assets/ subfolder) to understand its styling.figures_dir (returned by parse_paper) into the output folder.index.html that:
caption from parse_paper output and set <img src> to the figure file.src paths to use relative paths.render_html on generated page.review_html_visual on screenshot.If table images are present:
extract_table_html per table image.<img ...> with generated <table>...</table>.Ask user for final adjustments. If feedback is provided:
CLI tool (arxivterminal) for fetching, searching, and managing arXiv papers locally. Use when working with arXiv papers using the arxivterminal command - fetching new papers by category, searching the local database, viewing papers from specific dates, or managing the local paper database.
Fetch arXiv papers by date range and topics, rank them for research value, and produce introduction digests. Use when the user wants a literature sweep, daily or weekly paper triage, or a written overview of the best papers in a niche — without relying on the arxivterminal local database.
Search and analyze research papers, find related work, summarize key ideas. Use when user says "find papers", "related work", "literature review", "what does this paper say", or needs to understand academic papers.
AI paper reviewer. Use when the user says 'review my paper', 'help me review this paper', '审稿', 'give me feedback on my paper', 'check my manuscript', 'evaluate this paper for NeurIPS/ICLR/EuroSys'. Accepts PDF files and produces structured narrative reviews with venue-specific dimensional scores and Accept/Reject recommendation.
Convert a local paper PDF to structured Markdown and export all figures as PNG + SVG + drawio. Attempts editable figure reconstruction via the built-in autofigure pipeline (SAM3 → RMBG-2.0 → VLM → SVG), falling back to a layered-SVG wrapper when API keys are unavailable. Use when the user wants to parse a paper PDF, extract its text as Markdown, or get editable/exportable figure assets.
Convert raster figure images into editable DrawIO files using SAM3 segmentation, RMBG-2.0 background removal, and multimodal LLM drawio generation.