Skill · #97 most installed

baoyu-translate

JimLiu/baoyu-skills/skills/baoyu-translate

Translates articles and documents between languages with three modes - quick (direct), normal (analyze then translate), and refined (analyze, translate, review, polish). Supports custom glossaries and terminology consistency via EXTEND.md. Use when user asks to "translate", "翻译", "精翻", "translate article", "translate to Chinese/English", "改成中文", "改成英文", "convert to Chinese", "localize", "本地化", or needs any document translation. Also triggers for "refined translation", "精细翻译", "proofread translation", "快速翻译", "å¿«ç¿»", "è¿™ç¯‡æ–‡ç« ç¿»è¯‘ä¸€ä¸‹", or when a URL or file is provided with translation intent.

Installs
189
Repo stars
14k
Updated
7mo ago

Get started

Install this skill

npx skills add JimLiu/baoyu-skills --skill baoyu-translate

Installs into Claude Code, Codex, Cursor, OpenCode and the other agents it finds on your machine.

What your agent reads

SKILL.md

View on GitHub ↗

Translator

User Input Tools

When this skill prompts the user, follow this tool-selection rule (priority order):

  1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
  2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
  3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.

Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.

Script Directory

{baseDir} = this SKILL.md's directory. ${BUN_X} = bun if installed; else npx -y bun if npx available; else suggest installing bun. Replace {baseDir} and ${BUN_X} with actual values.

Script Purpose
scripts/main.ts CLI entry point. Default action splits markdown into chunks; also supports explicit chunk subcommand
scripts/chunk.ts Markdown chunking implementation used by main.ts and kept compatible for direct invocation

Preferences (EXTEND.md)

First one found wins:

Priority Path Scope
1 .baoyu-skills/baoyu-translate/EXTEND.md Project
2 ${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-translate/EXTEND.md XDG
3 $HOME/.baoyu-skills/baoyu-translate/EXTEND.md User home
  • Found → read and apply. On first use in a session, remind briefly: "Using preferences from [path]. You can edit EXTEND.md to customize glossary, audience, etc."
  • Not found → BLOCKING first-time setup before any translation; never silently use defaults. Ask all questions in references/config/first-time-setup.md (target language, mode, audience, style, save location) in ONE call, write EXTEND.md at the chosen location, confirm "Preferences saved to [path]", then continue.

Supports: target language, mode, audience, glossaries (inline or file path), style, chunk settings. Schema: references/config/extend-schema.md.

Defaults

EXTEND.md overrides defaults; CLI flags override EXTEND.md.

Setting Default EXTEND.md key CLI flag
Target language zh-CN target_language --to
Mode normal default_mode --mode
Audience general audience --audience
Style storytelling style --style
Chunk threshold (words, triggers chunking) 4000 chunk_threshold —
Chunk max words 5000 chunk_max_words —

Modes

Mode Flag Steps When to Use
Quick --mode quick Translate Short texts, informal content, quick tasks
Normal --mode normal (default) Analyze → Translate Articles, blog posts, general content
Refined --mode refined Analyze → Translate → Review → Polish Publication-quality, important documents

Auto-detection: "快翻", "quick", "直接翻译" → quick; "精翻", "refined", "publication quality", "proofread" → refined; otherwise the default mode.

Style presets (voice and tone, independent of audience; custom descriptions accepted, e.g. --style "poetic and lyrical"):

Value Description Effect
storytelling Engaging narrative flow (default) Draws readers in, smooth transitions, vivid phrasing
formal Professional, structured Neutral tone, clear organization, no colloquialisms
technical Precise, documentation-style Concise, terminology-heavy, minimal embellishment
literal Close to original structure Minimal restructuring, preserves source sentence patterns
academic Scholarly, rigorous Formal register, complex clauses OK, citation-aware
business Concise, results-focused Action-oriented, executive-friendly, bullet-point mindset
humorous Preserves and adapts humor Witty, playful, recreates comedic effect in target language
conversational Casual, spoken-like Friendly, approachable, as if explaining to a friend
elegant Literary, polished prose Aesthetically refined, rhythmic, carefully crafted word choices

Audience presets (custom descriptions accepted, e.g. --audience "AI感兴趣的普通读者"):

Value Description Effect
general General readers (default) Plain language, more translator's notes for jargon
technical Developers / engineers Less annotation on common tech terms
academic Researchers / scholars Formal register, precise terminology
business Business professionals Business-friendly tone, explain tech concepts

Workflow

Step 1: Load Preferences

  1. Check EXTEND.md (see Preferences)
  2. Load the built-in glossary for the language pair if available — EN→ZH: references/glossary-en-zh.md
  3. Merge glossaries: EXTEND.md glossary (inline) + glossary_files (paths relative to EXTEND.md) + built-in + --glossary file (CLI overrides all)

Step 2: Materialize Source & Create Output Directory

Materialize the source (file as-is; inline text/URL → translate/{slug}.md), then create {source-dir}/{source-basename}-{target-lang}/. Detect source language if --from is not given. Details and conflict handling: references/workflow-mechanics.md.

All intermediate and final files go in the output directory:

File Mode Description
translation.md All Final translation (always this name)
01-analysis.md Normal, Refined Content analysis (domain, tone, terminology)
02-prompt.md Normal, Refined Assembled translation prompt
03-draft.md Refined Initial draft before review
04-critique.md Refined Critical review findings (diagnosis only)
05-revision.md Refined Revised translation based on critique
chunks/ Chunked Source chunks + translated chunks

Step 3: Assess Content Length

Quick mode never chunks. If content exceeds the chunk threshold, warn: "This article is ~{N} words. Quick mode translates in one pass without chunking — for long content, --mode normal produces better results with terminology consistency." Proceed if the user doesn't switch.

Normal/refined: below threshold → translate as a single unit; at or above → chunked translation (3.1).

3.1 Long Content Preparation (normal/refined, ≥ threshold)

  1. Extract terminology across the whole document (proper nouns, technical terms, recurring phrases)
  2. Build session glossary: merge extracted terms with loaded glossaries, fix consistent translations
  3. Split: ${BUN_X} {baseDir}/scripts/main.ts <file> [--max-words <chunk_max_words>] [--output-dir <output-dir>] — splits at markdown block boundaries (headings, paragraphs, lists, code blocks, tables, etc.); an oversized single block falls back to line, then word splitting
  4. Assemble prompt: read 01-analysis.md (if it exists) and build shared context with Part 1 of references/subagent-prompt-template.md, inlining target style, content background, merged glossary, and translation challenges. Save as 02-prompt.md (shared context only, no task instructions)
  5. Draft via subagents (if an Agent tool is available):
    • One subagent per chunk, all in parallel (Part 2 of the template). Each reads 02-prompt.md, gets its position (chunk N of M + brief context of where it sits in the argument), and saves chunks/chunk-NN-draft.md
    • Consistency comes from the shared 02-prompt.md (glossary, figurative language mapping, comprehension challenges, source voice, translation challenges)
    • No chunks (under threshold): one subagent for the whole source file
    • No Agent tool: translate chunks sequentially inline using 02-prompt.md
  6. Merge chunks in order after all subagents finish; prepend chunks/frontmatter.md if it exists. Save as 03-draft.md (refined) or translation.md (normal)
  7. Keep all intermediate files in chunks/

After merging, the main agent takes over for review, revision, and polish (Step 4).

Step 4: Translate & Refine

Translation principles (all modes):

  • Rewrite, not translate: write natural, engaging target language as if a skilled native writer composed it. Test: "Does this read like it was originally written in the target language?"
  • Accuracy first: facts, data, and logic match the original exactly
  • Natural flow: idiomatic target word order; break long source sentences into shorter ones; render metaphors and idioms by intended meaning, not word-for-word
  • Terminology: standard translations, used consistently; annotate specialized terms with the original in parentheses on first occurrence
  • Preserve format: all markdown formatting (headings, bold, italic, images, links, code blocks)
  • Proactive interpretation: for jargon or concepts the audience may lack context for, add concise explanations in bold parentheses (**解释**) — few, only where genuinely needed
  • Frontmatter (if the source has YAML frontmatter): rename source-metadata fields with a source prefix (camelCase: url→sourceUrl, title→sourceTitle, etc.), add translated values as new top-level fields (skip title if the body has an H1), keep other fields as-is

Quick: translate directly → translation.md.

Normal:

  1. Analyze → 01-analysis.md (domain, tone, terminology, translation challenges)
  2. Assemble prompt → 02-prompt.md (instructions with context, glossary, challenges)
  3. Translate following 02-prompt.md → translation.md

Then tell the user: "Translation saved. To further review and polish, reply 继续润色 or refine." If they do, run refined Steps 4-6 on the existing output: rename current translation.md to 03-draft.md, then write 04-critique.md, 05-revision.md, and an updated translation.md.

Refined — per-step guidelines in references/refined-workflow.md. Each step reads the previous step's file:

  1. Analyze → 01-analysis.md
  2. Assemble prompt → 02-prompt.md (instructions with inlined context)
  3. Draft → 03-draft.md (with translator's notes; from subagents if chunked)
  4. Critical review → 04-critique.md (diagnosis only: accuracy, Europeanized language, strategy execution, expression issues)
  5. Revision → 05-revision.md (apply all critique findings)
  6. Polish → translation.md (publication quality)

Subagents (Step 3.1) only produce the initial draft. Review, revision, and polish belong to the main agent, which may delegate to subagents at its discretion.

Step 5: Output

Final translation is always translation.md in the output directory.

Then run a lightweight image-language pass: collect image references, identify likely text-heavy ones (covers, screenshots, diagrams, charts, frameworks, infographics), and list any whose main text language likely differs from the translated article. List only — do not localize images unless the user asks. Use the article's own image syntax (markdown or wikilink):

Possible image localization needed:
- ![example cover](attachments/example-cover.png): likely still contains source-language text while the article is now in target language
- ![example diagram](attachments/example-diagram.png): likely text-heavy framework graphic, check whether labels need translation

Summary:

**Translation complete** ({mode} mode)

Source: {source-path}
Languages: {from} → {to}
Output dir: {output-dir}/
Final: {output-dir}/translation.md
Glossary terms applied: {count}

If candidates were found, append after the summary a short note that some embedded images may still need image-text localization, followed by the list.

Extension Support

Custom configurations via EXTEND.md — see Preferences above.