Download skills/baoyu-translate/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does baoyu-translate live?
The publisher keeps it at https://github.com/JimLiu/baoyu-skills.
Which agents can use baoyu-translate?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
>-
name: baoyu-translate
description: >-
This skill should be used when the user asks to "translate", "翻译", "精翻", "translate article",
"translate to Chinese", "translate to English", "改成中文", "改成英文", "convert to Chinese",
"localize", "本地化", "refined translation", "精细翻译", "proofread translation", "快速翻译", "快翻",
"这篇文章翻译一下", or provides a URL/file with translation intent. Supports three modes
(quick/normal/refined) with custom glossary support.
version: 1.117.3
metadata:
openclaw:
homepage: https://github.com/JimLiu/baoyu-skills#baoyu-translate
requires:
anyBins:
- bun
- npx
Translator
Three-mode translation skill: quick for direct translation, normal for analysis-informed translation, refined for full publication-quality workflow with review and polish.
User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
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.
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
Scripts in scripts/ subdirectory. {baseDir} = this SKILL.md's directory path. Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; 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)
Check EXTEND.md in priority order — the first one found wins:
Read, parse, apply. On first use in session, briefly remind: "Using preferences from [path]. You can edit EXTEND.md to customize glossary, audience, etc."
Not found
MUST run first-time setup (see below) — do NOT silently use defaults
Use AskUserQuestion with all questions (target language, mode, audience, style, save location) in ONE call. After user answers, create EXTEND.md at the chosen location, confirm "Preferences saved to [path]", then continue.
Defaults
All configurable values in one place. EXTEND.md overrides these; CLI flags override EXTEND.md.
Setting
Default
EXTEND.md key
CLI flag
Description
Target language
zh-CN
target_language
--to
Translation target language
Mode
normal
default_mode
--mode
Translation mode
Audience
general
audience
--audience
Target reader profile
Style
storytelling
style
--style
Translation style preference
Chunk threshold
4000
chunk_threshold
—
Word count to trigger chunked translation
Chunk max words
5000
chunk_max_words
—
Max words per chunk
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
Default mode: Normal (can be overridden in EXTEND.md default_mode setting).
Style presets — control the voice and tone of the translation (independent of audience):
Value
Description
Effect
storytelling
Engaging narrative flow (default)
Draws readers in, smooth transitions, vivid phrasing
formal
Professional, structured
Neutral tone, clear organization, no colloquialisms
Materialize source (file as-is, inline text/URL → save to translate/{slug}.md), then create output directory: {source-dir}/{source-basename}-{target-lang}/. Detect source language if --from not specified.
Output directory contents (all intermediate and final files go here):
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 does not chunk — translate directly regardless of length. Before translating, estimate word count. If content exceeds chunk threshold (default 4000 words), proactively 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." Then proceed if user doesn't switch.
For normal and refined modes:
Content
Action
< chunk threshold
Translate as single unit
>= chunk threshold
Chunk translation (see Step 3.1)
3.1 Long Content Preparation (normal/refined modes, >= chunk threshold only)
Splits at markdown block boundaries to preserve structure
If a single block exceeds the threshold, falls back to line splitting, then word splitting
Assemble translation prompt:
Main agent reads 01-analysis.md (if exists) and assembles shared context using Part 1 of references/subagent-prompt-template.md — inlining: target style, content background, merged glossary, and translation challenges
Save as 02-prompt.md in the output directory (shared context only, no task instructions)
Draft translation via subagents (if Agent tool available):
Spawn one subagent per chunk, all in parallel (Part 2 of the template)
Each subagent reads 02-prompt.md for shared context, receives chunk position info (chunk N of M + brief context of where it sits in the argument), translates its chunk, saves to chunks/chunk-NN-draft.md
Consistency is guaranteed by the shared 02-prompt.md (glossary, figurative language mapping, comprehension challenges, source voice, and translation challenges from analysis)
If no chunks (content under threshold): spawn one subagent for the entire source file
If Agent tool is unavailable, translate chunks sequentially inline using 02-prompt.md
Merge: Once all subagents complete, combine translated chunks in order. If chunks/frontmatter.md exists, prepend it. Save as 03-draft.md (refined) or translation.md (normal)
All intermediate files (source chunks + translated chunks) are preserved in chunks/
After chunked draft is merged, return control to main agent for critical review, revision, and polish (Step 4).
Step 4: Translate & Refine
Translation principles (apply to all modes):
Rewrite, not translate: Rewrite content into natural, engaging target language as if a skilled native writer composed it from scratch. Quality test: "Does this read like it was originally written in the target language?"
Accuracy first: Facts, data, and logic must match the original exactly
Natural flow: Use idiomatic target language word order. Break long source sentences into shorter, natural ones. Interpret metaphors and idioms by intended meaning, not word-for-word
Terminology: Use standard translations consistently. First occurrence of specialized terms: annotate with original in parentheses
Proactive interpretation: For jargon or concepts the target audience may lack context for, add concise explanations in bold parentheses（**解释**）. Keep annotations few — only where genuinely needed for comprehension
Frontmatter: If source has YAML frontmatter, rename source-metadata fields with source prefix (camelCase: url→sourceUrl, title→sourceTitle, etc.), add translated values as new top-level fields (skip title if body has H1), keep other fields as-is
Quick Mode
Translate directly → save to translation.md. Apply all translation principles above.
After completion, prompt user: "Translation saved. To further review and polish, reply 继续润色 or refine."
If user continues, proceed with critical review → revision → polish (same as refined mode Steps 4-6 below), saving 03-draft.md (rename current translation.md), 04-critique.md, 05-revision.md, and updated translation.md.
The subagent (if used in Step 3.1) only handles the initial draft. All subsequent steps (critical review, revision, polish) are handled by the main agent, which may delegate to subagents at its discretion.
Each step reads the previous step's file and builds on it.
Step 5: Output
Final translation is always at translation.md in the output directory.
After the final translation is written, do a lightweight image-language pass:
Collect image references from the translated article
Identify likely text-heavy images such as covers, screenshots, diagrams, charts, frameworks, and infographics
If any image likely contains a main text language that does not match the translated article language, proactively remind the user
The reminder must be a list only. Do not automatically localize those images unless the user asks
Reminder format (use whatever image syntax the article already uses — standard markdown or wikilink):
Possible image localization needed:
- : likely still contains source-language text while the article is now in target language
- : likely text-heavy framework graphic, check whether labels need translation
If mismatched image-language candidates were found, append a short note after the summary telling the user that some embedded images may still need image-text localization, followed by the candidate list.
Extension Support
Custom configurations via EXTEND.md. See Preferences section for paths and supported options.
How do I install baoyu-translate?
Download skills/baoyu-translate/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does baoyu-translate live?
The publisher keeps it at https://github.com/JimLiu/baoyu-skills.
Which agents can use baoyu-translate?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.