--- name: md2htmlnote description: 'Use when a MinerU-exported Markdown paper with images and LaTeX needs an HTML study report or a full bilingual parallel-reading page with semantic colors. Triggers: HTML阅读笔记, 核心解读, 学习汇报, 双语阅读, 对照翻译, 语义标注, 颜色编码, bilingual reading, parallel translation, comparative reading.' --- # Markdown to HTML Reading Page Produce one HTMLnote that opens with **文献鸟瞰** and switches between the paper graph, paper-specific flow, layered reading and **精读解析**. Select one of two content modes for the complete analytical reader: | Request | Mode | Read next | Locked template | Verifier | | --- | --- | --- | --- | --- | | Ordinary HTML note, core interpretation, advisor/study report; no explicit bilingual request | **report (default)** | [Report rules](references/report.md) | `template.html` | `verify.py` | | Explicit bilingual / parallel reading / 对照翻译 / 双语, or semantic color annotation | **bilingual** | [Bilingual rules](references/bilingual.md) | `bilingual/template.html` | `bilingual/verify.py` | An explicit bilingual request selects bilingual resources even when it also mentions notes, interpretation, or a report. If both outputs are requested, produce and verify each separately. Bilingual term annotations alone retain report mode. Modes are authoring choices, not script flags. Read [Common rules](references/common.md), [reading experience](references/reading-experience.md), and the selected mode's reference, then read its actual template before assembly. All command paths are relative to this skill root. Use the root `link_images.py` and `embed_base64.py` in either mode; do not look for copies under `bilingual/`. 1. Resolve the paper's source and HTML version through `_tmp/MANIFEST.json`: registered `linked_fixed_md` first, otherwise `linked_md`. Write to the registered `P/html/versions//` output and respect the registered `html/current.json` pointer. Details are in the common rules. 2. Copy the selected template's CSS, wrappers, controls, and JavaScript exactly; fill only content slots. Preserve all substantive source content and audit figures, tables, formulas, references, and back matter. Build a source-grounded term dictionary and mark recurring technical terms, abbreviations and parameter headers for hover/focus/tap explanations. Place each figure/table after its explanatory paragraph in the corresponding body section; keep original numbers, units and data. See the shared reading contract for the exact markup and placement recipe. 3. Apply only the selected mode's content contract. **Report:** Chinese interpretation with `.insight` boxes and sequential explicit `\tag{1}`, `\tag{2}`, … on every display formula. **Bilingual:** full original/Chinese paragraph pairs, two-level semantic colors, `.insight-note` analysis, and working toggles; preserve source equation tags and allow originally unnumbered derivations. English original text and captions are required in bilingual mode. 4. Save the complete reader to an authoring file. Follow [Four-view HTMLnote](references/multiview.md) to write the paper-specific guide JSON. Run `build_multiview.py reader.html guides.json -o ` (add `--pdf ` when available). Deliver the resulting single file by default. When explicitly asked for the standalone reader, deliver the selected content-mode output directly. 5. Run **only the selected content mode's verifier** on the registered output with its resolved source Markdown. Check the guide claims, evidence, reader anchors and PDF pages against the same paper. 6. Perform native visual QA: open the real artifact, check loaded DOM, images and MathJax, inspect desktop/mobile screenshots and controls, crop uncertain regions, fix the generation source and re-render. The concise procedure and failure reporting are in [Common rules](references/common.md#native-visual-qa). Follow a guide link to its specific section, figure or table, then return and check the selected node, stage or expanded topics. Return the mode, versioned artifact path, source path, verifier result, visual checks performed, and any unresolved or unverified items. Do not claim visual or formula-rendering success from a structural pass alone.