--- name: active-research description: Deep research and analysis tool. Generates comprehensive HTML reports on any topic, domain, paper, or technology. Use when user asks to research, analyze, investigate, deep-dive, or generate a report on any subject. Supports academic papers (arXiv), technologies, trends, comparisons, and general topics. --- # Active Research Analyze any topic, domain, or paper and generate a beautiful HTML report using Actionbook browser automation and json-ui rendering. ## Usage ``` /active-research /active-research --lang zh /active-research --output ./reports/my-report.json ``` Or simply tell Claude: "帮我深度研究 XXX 并生成报告" / "Research XXX and generate a report" ### Parameters | Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | `topic` | Yes | - | The subject to research (any text) | | `--lang` | No | `both` | Language: `en`, `zh`, or `both` (bilingual) | | `--output` | No | `./output/.json` | Output path for JSON report | ### Topic Detection | Pattern | Type | Strategy | |---------|------|----------| | `arxiv:XXXX.XXXXX` | Paper | **arXiv Advanced Search** (Step 2b) + ar5iv deep read | | `doi:10.XXX/...` | Paper | Resolve DOI, then **arXiv Advanced Search** for related work | | Academic keywords (paper, research, model, algorithm) | Academic topic | **arXiv Advanced Search** (Step 2b) + Google for non-academic sources | | URL | Specific page | Fetch and analyze the page | | General text | Topic research | Google search + arXiv Advanced Search if relevant | ## Architecture ``` ┌──────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────┐ │ Claude │────▶│ Actionbook │────▶│ Web Pages │────▶│ Extract │ │ Code │ │ Browser CLI │ │ (multiple) │ │ Content │ └──────────┘ └──────────────┘ └──────────────┘ └─────┬────┘ │ │ │ ┌──────────────┐ ┌──────────────┐ │ ├─────────▶│ Actionbook │ │ arXiv Adv. │ │ │ │ search/get │────▶│ Search Form │──────────▶│ │ │ (selectors) │ │ (40+ fields) │ │ │ └──────────────┘ └──────────────┘ │ │ │ │ Actionbook indexes arXiv form selectors, │ │ enabling field-specific, filtered academic │ │ searches that WebFetch/WebSearch CANNOT do. │ │ │ ┌──────────┐ ┌──────────────┐ ┌──────────────┐ │ │ Open in │◀────│ json-ui │◀────│ Write JSON │◀──────────┘ │ Browser │ │ render │ │ Report │ Synthesize └──────────┘ └──────────────┘ └──────────────┘ ``` ### Why Actionbook, Not WebFetch/WebSearch? | Capability | Actionbook | WebFetch/WebSearch | |------------|-----------|-------------------| | Operate complex web forms (dropdowns, checkboxes, date pickers) | Yes — uses indexed selectors | No | | arXiv: search by Author, Title, Abstract separately | Yes — `#terms-0-field` select | No — keyword only | | arXiv: filter by subject (CS, Physics, Math, ...) | Yes — category checkboxes | No | | arXiv: filter by date range or specific year | Yes — date inputs | No | | Read pages with verified selectors (no guessing) | Yes — `actionbook get` | No — raw HTML parse | | Interact with any indexed site's UI | Yes — click, type, select | No — read-only | **This is the core value of Actionbook for research: it turns web forms into structured, programmable interfaces for AI agents.** ## MUST USE Actionbook CLI **Always use `actionbook browser` commands for web browsing. Never use WebFetch or WebSearch.** ```bash actionbook browser open # Navigate to page actionbook browser snapshot # Get accessibility tree actionbook browser text [selector] # Extract text content actionbook browser screenshot [path] # Capture visual actionbook browser click # Click element actionbook browser close # Close browser (ALWAYS do this at end) ``` ## Complete Workflow ### Step 1: Plan Search Strategy Based on the topic, generate 5-8 search queries from different angles: - Core definition / overview - Latest developments / news - Technical details / implementation - Comparisons / alternatives - Expert opinions / analysis - Use cases / applications **Search order — ALWAYS query Actionbook API first, then search:** | Step | Action | Why | |------|--------|-----| | **Step 2 (FIRST)** | **Query Actionbook API** | Get verified selectors for arXiv Advanced Search form, ar5iv papers, and any other known sites BEFORE browsing. This is the foundation for all subsequent steps. | | **Step 3 (SECOND)** | **arXiv Advanced Search** | Use Actionbook selectors from Step 2 to perform multi-field, filtered academic search. Even non-academic topics often have relevant papers. | | **Step 4 (THIRD)** | Google / Bing search | Supplement with blogs, news, code, discussions, non-academic sources. | **IMPORTANT:** Always query Actionbook API first (Step 2) to get selectors, then use them in arXiv Advanced Search (Step 3). This is what makes Actionbook-powered research fundamentally different from WebFetch/WebSearch — the agent knows the exact selectors for every form field before it even opens the browser. ### Step 2: Query Actionbook API for Selectors (ALWAYS DO THIS FIRST) **BEFORE browsing any URL, query Actionbook's indexed selectors.** This gives you verified CSS/XPath selectors instead of guessing. ```bash # Search for indexed actions by domain actionbook search "" -d "" # Get detailed selectors for a specific page actionbook get ":/:" ``` **Pre-indexed sites useful for research:** | Site | area_id | Key Selectors | |------|---------|---------------| | arXiv Advanced Search | `arxiv.org:/search/advanced:default` | **40+ selectors**: field select, term input, category checkboxes (CS/Physics/Math/...), date range filters, cross-list control — used in Step 3 | | ar5iv paper | `ar5iv.labs.arxiv.org:/html/{paper_id}:default` | `h1.ltx_title_document` (title), `div.ltx_authors` (authors), `div.ltx_abstract` (abstract), `section.ltx_section` (sections) | | Google Scholar | `scholar.google.com:/:default` | `#gs_hdr_tsi` (search input), `#gs_hdr_tsb` (search button) | | arXiv homepage | `arxiv.org:/:default` | Global search across 2.4M+ articles | **For any URL you plan to visit**, run `actionbook search "" -d ""` to check if it's indexed. Use indexed selectors when available; fall back to `actionbook browser snapshot` for unindexed sites. **Example: Get arXiv Advanced Search selectors before searching:** ```bash # Query Actionbook for arXiv form selectors actionbook get "arxiv.org:/search/advanced:default" # Returns 40+ selectors: #terms-0-field, #terms-0-term, #classification-computer_science, etc. ``` ### Step 3: arXiv Advanced Search (Using Actionbook Selectors) > **Key differentiator:** WebFetch/WebSearch can only do simple keyword searches. Actionbook has indexed the **entire arXiv Advanced Search form** with 40+ verified selectors (queried in Step 2), enabling multi-field, multi-criteria academic searches — just like a human researcher would use the form. Using the selectors obtained from Step 2, the Agent can: | Capability | Actionbook Selector | WebFetch/WebSearch | |------------|--------------------|--------------------| | Search by specific field (Title, Author, Abstract) | `#terms-0-field` select → choose field | Not possible | | Add multiple search terms with boolean logic | `button "Add another term +"` | Not possible | | Filter by subject (CS, Physics, Math, etc.) | `#classification-computer_science` checkbox | Not possible | | Filter by date range | `#date-filter_by-3` radio + `#date-from_date` / `#date-to_date` | Not possible | | Filter by specific year | `#date-filter_by-2` radio + `#date-year` input | Not possible | | Include/exclude cross-listed papers | `#classification-include_cross_list-0/1` radio | Not possible | | Control results display | `#size` select, `#abstracts-0/1` radio | Not possible | **Example: Search for recent CS papers by a specific author:** ```bash # Open arXiv Advanced Search actionbook browser open "https://arxiv.org/search/advanced" # 1. Set search field to "Author" and type author name actionbook browser click "#terms-0-field" actionbook browser click "option[value='author']" actionbook browser type "#terms-0-term" "Yann LeCun" # 2. Filter to Computer Science only actionbook browser click "#classification-computer_science" # 3. Restrict to past 12 months actionbook browser click "#date-filter_by-1" # 4. Show abstracts in results actionbook browser click "#abstracts-0" # 5. Submit search actionbook browser click "button:has-text('Search'):nth(2)" # 6. Extract results actionbook browser text "#main-container" ``` **Example: Search by title keywords in a date range:** ```bash actionbook browser open "https://arxiv.org/search/advanced" # Search in "Title" field actionbook browser click "#terms-0-field" actionbook browser click "option[value='title']" actionbook browser type "#terms-0-term" "large language model agent" # Date range: 2025-01 to 2026-02 actionbook browser click "#date-filter_by-3" actionbook browser type "#date-from_date" "2025-01-01" actionbook browser type "#date-to_date" "2026-02-09" # Submit and extract actionbook browser click "button:has-text('Search'):nth(2)" actionbook browser text "#main-container" ``` ### Step 4: Supplement with Google / Bing Search After arXiv, use Google/Bing to find non-academic sources (blogs, news, docs, code, discussions): ```bash # Search via Google actionbook browser open "https://www.google.com/search?q=" actionbook browser text "#search" # Or search via Bing actionbook browser open "https://www.bing.com/search?q=" actionbook browser text "#b_results" ``` Parse the search results to extract URLs and snippets. Collect the top 5-10 most relevant URLs. For each discovered URL, query Actionbook API (Step 2 pattern) to check if the site is indexed before visiting. ### Step 5: Deep Read Sources For each relevant URL, **first query Actionbook API** (same as Step 2) to check if the site is indexed, then use verified selectors: ```bash actionbook browser open "" actionbook browser text # Full page text (fallback) actionbook browser text "" # Use Actionbook selector if indexed ``` **For arXiv papers**, try sources in this order (newer papers often fail on ar5iv): ```bash # 1. Try ar5iv first (best structured selectors from Actionbook) actionbook browser open "https://ar5iv.org/html/" actionbook browser text "h1.ltx_title_document" # Title actionbook browser text "div.ltx_authors" # Authors actionbook browser text "div.ltx_abstract" # Abstract # NOTE: section.ltx_section often fails on newer papers — use "article" as fallback # 2. If ar5iv content is truncated (<5KB), fall back to arxiv abstract + other sources actionbook browser open "https://arxiv.org/abs/" actionbook browser text "main" # 3. Supplement with HuggingFace model cards and GitHub READMEs for full details actionbook browser open "https://huggingface.co/papers/" actionbook browser text "main" ``` **Key lesson:** Don't rely solely on ar5iv. Always cross-reference 3-4 sources for completeness. **For Google Scholar** (indexed by Actionbook): ```bash actionbook browser open "https://scholar.google.com" # Type into search: use selector #gs_hdr_tsi actionbook browser click "#gs_hdr_tsi" # ... type query, click #gs_hdr_tsb to search ``` **For unindexed sites**, use snapshot to discover page structure: ```bash actionbook browser open "" actionbook browser snapshot # Get accessibility tree to find selectors actionbook browser text "" ``` ### Step 6: Synthesize Findings Organize collected information into a coherent report: 1. Overview / Executive Summary 2. Key Findings 3. Detailed Analysis 4. Supporting Data / Evidence 5. Implications / Significance 6. Sources ### Step 7: Generate json-ui JSON Report Write a JSON file following the `@actionbookdev/json-ui` schema. Use the Write tool. **Output path:** `./output/.json` (or user-specified `--output` path) ### Step 8: Render HTML **CRITICAL: You MUST try ALL fallback methods before giving up. Do NOT stop at the first failure.** **IMPORTANT: Always use ABSOLUTE paths for JSON_FILE and HTML_FILE.** Relative paths break when git rev-parse returns an absolute repo root. Try each method one by one until one succeeds: ```bash # Method 1: npx (recommended — works anywhere if npm is available) npx @actionbookdev/json-ui render /absolute/path/to/report.json -o /absolute/path/to/report.html # Method 2: Global install (if user ran: npm install -g @actionbookdev/json-ui) json-ui render /absolute/path/to/report.json -o /absolute/path/to/report.html # Method 3: Monorepo local path (fallback if inside actionbook project) node "$(git rev-parse --show-toplevel)/packages/json-ui/dist/cli.js" render /absolute/path/to/report.json -o /absolute/path/to/report.html ``` **NEVER give up silently.** If all methods fail, tell the user: 1. The JSON report is saved at `` 2. To install the renderer, run: `npm install -g @actionbookdev/json-ui` ### Step 9: Open in Browser ```bash # macOS open # Linux xdg-open ``` ### Step 10: Close Browser **Always close the browser when done:** ```bash actionbook browser close ``` ## json-ui Report Template **IMPORTANT: Always include BrandHeader and BrandFooter.** ```json { "type": "Report", "props": { "theme": "auto" }, "children": [ { "type": "BrandHeader", "props": { "badge": { "en": "Deep Research Report", "zh": "深度研究报告" }, "poweredBy": "Actionbook" } }, { "type": "Section", "props": { "title": { "en": "Overview", "zh": "概述" }, "icon": "paper" }, "children": [ { "type": "Prose", "props": { "content": { "en": "English overview...", "zh": "中文概述..." } } } ] }, { "type": "Section", "props": { "title": { "en": "Key Findings", "zh": "核心发现" }, "icon": "star" }, "children": [ { "type": "ContributionList", "props": { "items": [ { "badge": { "en": "Finding", "zh": "发现" }, "title": { "en": "...", "zh": "..." }, "description": { "en": "...", "zh": "..." } } ] } } ] }, { "type": "Section", "props": { "title": { "en": "Detailed Analysis", "zh": "详细分析" }, "icon": "bulb" }, "children": [ { "type": "Prose", "props": { "content": { "en": "...", "zh": "..." } } } ] }, { "type": "Section", "props": { "title": { "en": "Key Metrics", "zh": "关键指标" }, "icon": "chart" }, "children": [ { "type": "MetricsGrid", "props": { "metrics": [], "cols": 3 } } ] }, { "type": "Section", "props": { "title": { "en": "Sources", "zh": "信息来源" }, "icon": "link" }, "children": [ { "type": "LinkGroup", "props": { "links": [] } } ] }, { "type": "BrandFooter", "props": { "timestamp": "YYYY-MM-DDTHH:MM:SSZ", "attribution": "Powered by Actionbook", "disclaimer": { "en": "This report was generated by AI using web sources. Verify critical information independently.", "zh": "本报告由 AI 基于网络来源生成，请独立验证关键信息。" } } } ] } ``` ### Paper Report Template (for arXiv papers) When analyzing academic papers, use a richer template with: - `PaperHeader` (title, arxivId, date, categories) - `AuthorList` (authors with affiliations) - `Abstract` (with keyword highlights) - `ContributionList` (key contributions) - `MethodOverview` (step-by-step method) - `ResultsTable` (experimental results) - `Formula` (key equations, LaTeX) - `Figure` (paper figures from ar5iv) ### Available json-ui Components | Component | Use For | Key Props | |-----------|---------|-----------| | `BrandHeader` | Report header | `badge`, `poweredBy` | | `PaperHeader` | Paper metadata | `title`, `arxivId`, `date`, `categories` | | `AuthorList` | Authors | `authors: [{name, affiliation}]`, `maxVisible` | | `Section` | Major section | `title`, `icon` (paper/star/bulb/chart/code/link/info/warning) | | `Prose` | Rich text | `content` (supports **bold**, *italic*, `code`, lists) | | `Abstract` | Abstract text | `text`, `highlights: ["keyword"]` | | `ContributionList` | Numbered findings | `items: [{badge, title, description}]` | | `MethodOverview` | Step-by-step | `steps: [{step, title, description}]` | | `MetricsGrid` | Key stats | `metrics: [{label, value, trend, suffix}]`, `cols` | | `ResultsTable` | Data table | `columns`, `rows`, `highlights: [{row, col}]` | | `Table` | Generic table | `columns: [{key, label}]`, `rows`, `striped`, `compact` | | `Callout` | Info/tip/warning | `type` (info/tip/warning/important/note), `title`, `content` | | `Highlight` | Blockquote | `type` (quote/important/warning/code), `text`, `source` | | `KeyPoint` | Key finding card | `icon`, `title`, `description`, `variant` | | `CodeBlock` | Code snippet | `code`, `language`, `title`, `showLineNumbers` | | `Formula` | LaTeX equation | `latex`, `block`, `label` | | `Figure` | Image(s) | `images: [{src, alt, width}]`, `label`, `caption` | | `Image` | Single image | `src`, `alt`, `caption`, `width` | | `DefinitionList` | Term/definition | `items: [{term, definition}]` | | `LinkGroup` | Source links | `links: [{href, label, icon}]` | | `Grid` | Grid layout | `cols`, children | | `Card` | Card container | `padding` (sm/md/lg), `shadow` | | `TagList` | Tags | `tags: [{label, color, href}]` | | `BrandFooter` | Footer | `timestamp`, `attribution`, `disclaimer` | ### json-ui Known Pitfalls | Pitfall | Symptom | Fix | |---------|---------|-----| | `MetricsGrid.suffix` as i18n object | `text.replace is not a function` | `suffix` must be a **plain string**, not `{ "en": ..., "zh": ... }` | | `MetricsGrid.value` as number | Render error | `value` must be a **string** (e.g., `"58.5"` not `58.5`) | | Missing `BrandHeader`/`BrandFooter` | Report looks broken | Always include both | | `Table` row values as i18n object | `[object Object]` in cells | Row cell values must be **plain strings**. Column `label` supports i18n, but row data does not. Use `"Runtimes / 运行时"` instead of `{ "en": "Runtimes", "zh": "运行时" }` | | Very long Prose content | Truncated render | Split into multiple Prose blocks or use subsections | ### i18n Support All text fields support bilingual output **unless noted above**: ```json { "en": "English text", "zh": "中文文本" } ``` For `--lang en`, use plain strings. For `--lang zh`, use plain Chinese strings. For `--lang both` (default), use i18n objects. **Exceptions:** - `MetricsGrid` props `value` and `suffix` must always be plain strings. - `Table` row cell values must be plain strings (column `label` supports i18n, but row data does not). For bilingual, use `"English / 中文"` format. ## Academic Paper Support ### arXiv Papers **ar5iv.org HTML** (preferred for reading, but often incomplete for papers < 3 months old): | Element | Selector (Actionbook-verified) | Reliability | Fallback | |---------|-------------------------------|-------------|----------| | Title | `h1.ltx_title_document` | High | `div.ltx_abstract` includes title context | | Authors | `div.ltx_authors` | High | — | | Abstract | `div.ltx_abstract` | High | — | | Full article | `article` | Medium | Use when section selectors fail | | Sections | `section.ltx_section` | **Low on new papers** | `article` for all content | | Section title | `h2.ltx_title_section` | **Low on new papers** | Parse from `article` text | | Figures | `figure.ltx_figure` | Medium | — | | Tables | `table.ltx_tabular` | Medium | — | | Bibliography | `.ltx_bibliography` | Medium | — | **Note:** For papers submitted within the last ~3 months, ar5iv often renders incomplete content. Always check `actionbook browser text 2>&1 | wc -c` — if < 5KB, the page didn't fully render. Fall back to other sources. **arXiv API** (for metadata via actionbook browser): ``` actionbook browser open "http://export.arxiv.org/api/query?id_list={arxiv_id}" actionbook browser text ``` ### Recommended Source Priority for Papers Based on testing, use this priority order for maximum coverage: | Priority | Source | What you get | Reliability | |----------|--------|-------------|-------------| | 1 | `arxiv.org/abs/` | Abstract, metadata, submission history | Very high | | 2 | `huggingface.co/papers/` | Abstract, community comments, related models/datasets | Very high | | 3 | GitHub repo (from search results) | README with method details, model zoo, code | High | | 4 | HuggingFace model card | Training recipe, benchmark results, quick start | High | | 5 | `ar5iv.org/html/` | Full paper HTML with structured selectors | Medium (fails on new papers) | | 6 | Google Scholar / Semantic Scholar | Citations, related work | Medium | **Key insight:** Don't rely on a single source. The combination of arxiv abstract + HuggingFace + GitHub typically gives 90%+ of what you need, even when ar5iv fails. ### Other Academic Sources Use `actionbook browser` to visit and extract content from: - Google Scholar (`scholar.google.com`) — Actionbook indexed, use `#gs_hdr_tsi` for search - Semantic Scholar (`semanticscholar.org`) - Papers With Code (`paperswithcode.com`) - Conference proceedings sites ## Error Handling | Error | Action | |-------|--------| | Browser fails to open | Run `actionbook browser status`, retry | | Page load timeout (30s) | Skip source, try next. Common on papers.cool, slow academic sites | | ar5iv content truncated (<5KB) | Paper too new for ar5iv. Fall back to arxiv abstract + HuggingFace + GitHub | | `section.ltx_section` not found | ar5iv rendering incomplete. Use `actionbook browser text "article"` or `"main"` instead | | Actionbook selector not found | Use `actionbook browser snapshot` to discover actual page structure | | `actionbook search` returns no results | Site not indexed. Use `actionbook browser snapshot` to find selectors manually | | json-ui render crash (`text.replace`) | Check MetricsGrid `suffix`/`value` — must be plain strings, not i18n objects | | `npx @actionbookdev/json-ui` fails | Run `npm install -g @actionbookdev/json-ui` and retry with `json-ui render`. If still fails, try monorepo local path | | No search results | Broaden search terms, try different angles | | Render failed | Save JSON, tell user path, and suggest: `npm install -g @actionbookdev/json-ui` | **IMPORTANT:** Always run `actionbook browser close` before finishing, even on errors. ## Quality Guidelines 1. **Breadth**: Research from at least 3-5 diverse sources 2. **Depth**: Read full articles, not just snippets 3. **Accuracy**: Cross-reference facts across sources 4. **Structure**: Use appropriate json-ui components for each content type 5. **Attribution**: Always include source links in the report 6. **Freshness**: Prefer recent sources when relevance is equal ## Chinese Content Quality Guidelines (中文内容质量规范) **CRITICAL: Chinese text must be written as native Chinese, NOT translated from English.** The `zh` field is not a translation — it is an independent Chinese version of the content. Write it as if authoring a Chinese tech article from scratch. ### Common Problems to Avoid | Problem | Bad Example | Good Example | |---------|-------------|--------------| | 被动语态过多 | "Wasm 已被广泛采用" | "Wasm 已经大规模落地" | | 英语语序直译 | "广泛但常常不可见地被采用" | "已经深入渗透到各类产品中，只是用户浑然不觉" | | 生硬术语拼接 | "语言无关的异步通信" | "不绑定特定编程语言的异步通信机制" | | 直译英文短语 | "关键缺失部分" | "最后一块拼图" | | "地道"当形容词 | "地道绑定" | "符合各语言习惯的绑定" | | 逗号长句（一逗到底） | "A，B，C，D，E。" | 拆成 2-3 个短句 | | 引用原文硬翻 | "「许多用户并未意识到它正在被使用」" | 用中文重新表述引用的核心意思，必要时保留原文人名 | ### Writing Rules 1. **先写中文，再对照英文查漏**：不要从英文逐句翻译。先理解内容本质，用中文重新组织表达。 2. **主动语态优先**：中文天然偏好主动句。"X 被 Y 采用" → "Y 采纳了 X" 或 "Y 已在用 X"。 3. **短句 > 长句**：中文读者偏好短句。超过 40 字的句子应拆分。 4. **术语处理原则**： - 有公认中文译名的术语用中文：服务器 → 服务器、容器 → 容器、沙箱 → 沙箱 - 无公认译名的术语保留英文：Component Model、WASI、SIMD、Cold Start - 首次出现时中英对照：「组件模型（Component Model）」，之后可只用中文 - 不要硬造中文译名（如"非干扰分析"，应写"Noninterference 分析"或解释性表述） 5. **数据和事实保持一致**：中英文的数字、日期、引用来源必须完全一致。 6. **语气自然**：可以用"说白了"、"换句话说"、"简单来说"等口语化连接词，避免全篇书面腔。 7. **标点规范**：用中文标点（，。；：「」）而非英文标点。引号优先用「」。 ### Table & Short Text Rules (表格与短文本规则) Table 行中的 `"English / 中文"` 格式是中文质量的重灾区。短文本更容易暴露机翻痕迹。 **规则：中文部分必须是独立的中文表述，不是英文的逐词翻译。** | Bad | Why Bad | Good | |-----|---------|------| | "应用级错误处理" | 太生硬，像翻译腔 | "应用层统一报错" | | "高性能 Web 框架" | 可以，但太平淡 | "主打性能的 Web 框架" | | "序列化框架" | 可以接受 | "序列化框架" ✓ | | "嵌入式异步执行器" | 太绕 | "嵌入式异步运行器" | | "凸块分配器" | 硬造译名，没人这么说 | "Bump 分配器（arena 风格）" | | "安全内存擦除" | 太书面 | "安全清零内存" | | "多生产者多消费者通道" | 太长 | "MPMC 通道" | | "类 React UI 框架" | OK | "类 React 的 UI 框架" ✓ | **表格中文短文本的核心原则：** 1. **保留英文术语**：Bump allocator、MPMC、ECS 这些没有公认中文译名的概念，直接保留英文。别硬翻。 2. **口语化 > 书面化**：短文本读者扫一眼就过，要像说话一样自然。"主打性能" 比 "性能优化的" 好。 3. **别逐词翻译**：先理解英文描述的意思，然后用中文重新说一遍。"Full-featured datetime" → "功能齐全的时间日期库"，不是 "全功能日期时间"。 4. **可以省略冗余修饰**：英文 "A generic serialization/deserialization framework" → 中文只需 "序列化框架"。 5. **数量控制在 10 字以内**：表格中文描述尽量控制在 10 个汉字以内，简短精准。 ### Bilingual Tone Reference | English Tone | Chinese Equivalent | Example | |--------------|-------------------|---------| | "X has reached a critical milestone" | 不要直译"关键里程碑" | "X 迎来了重要转折点" 或 "X 进入成熟期" | | "This is the key missing piece" | 不要直译"关键缺失部分" | "这是最后一块拼图" 或 "补上了最关键的短板" | | "excels at cold starts" | 不要直译"在冷启动方面表现卓越" | "冷启动速度远超同类方案" | | "security scrutiny intensifies" | 不要直译"安全审查加强" | "安全领域的关注度持续升温" | | "emerging as a standard" | 不要直译"正成为标准" | "逐渐确立了标准地位" 或 "大有一统江湖之势" | | "widespread but invisible adoption" | 不要直译"广泛但不可见的采用" | "已经悄然渗透到各类产品中" |

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