SKILL.md
$2c
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:
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
Result
Action
Found
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
EXTEND.md supports: default target language, default mode, target audience, custom glossaries (inline or file path), translation style, chunk settings.
Schema: references/config/extend-schema.md.
First-Time Setup (BLOCKING)
CRITICAL: When EXTEND.md is not found, you MUST run the first-time setup before ANY translation. This is a BLOCKING operation.
Full reference: references/config/first-time-setup.md
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
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
Custom style descriptions are also accepted, e.g., --style "poetic and lyrical".
Auto-detection:
- "快翻", "quick", "直接翻译" → quick mode
- "精翻", "refined", "publication quality", "proofread" → refined mode
- Otherwise → default mode (normal)
Upgrade prompt: After normal mode completes, display:
Translation saved. To further review and polish, reply "继续润色" or "refine".
If user responds, continue with review → polish steps (same as refined mode Steps 4-6 in refined-workflow.md) on the existing output.
Audience presets:
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
Custom audience descriptions are also accepted, e.g., --audience "AI感兴趣的普通读者".
Workflow
Step 1: Load Preferences
1.1 Check EXTEND.md (see Preferences section above)
1.2 Load built-in glossary for the language pair if available:
- EN→ZH: references/glossary-en-zh.md
1.3 Merge glossaries: EXTEND.md glossary (inline) + EXTEND.md glossary_files (external files, paths relative to EXTEND.md location) + built-in glossary + --glossary file (CLI overrides all)
Step 2: Materialize Source & Create Output Directory
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.
Full details: references/workflow-mechanics.md
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)
Before translating chunks:
- Extract terminology: Scan entire document for proper nouns, technical terms, recurring phrases
- Build session glossary: Merge extracted terms with loaded glossaries, establish consistent translations
- Split into chunks: Use
${BUN_X} {baseDir}/scripts/main.ts <file> [--max-words <chunk_max_words>] [--output-dir <output-dir>]
- Parses markdown blocks (headings, paragraphs, lists, code blocks, tables, etc.)
- 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.mdin 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.mdfor shared context, receives chunk position info (chunk N of M + brief context of where it sits in the argument), translates its chunk, saves tochunks/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.mdexists, prepend it. Save as03-draft.md(refined) ortranslation.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
- Preserve format: Keep all markdown formatting (headings, bold, italic, images, links, code blocks)
- 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
sourceprefix (camelCase:url→sourceUrl,title→sourceTitle, etc.), add translated values as new top-level fields (skiptitleif body has H1), keep other fields as-is
#### Quick Mode
Translate directly → save to translation.md. Apply all translation principles above.
#### Normal Mode
- Analyze →
01-analysis.md(domain, tone, terminology, translation challenges)
- Assemble prompt →
02-prompt.md(translation instructions with context, glossary, challenges)
- Translate (following
02-prompt.md) →translation.md
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.
#### Refined Mode
Full workflow for publication quality. See references/refined-workflow.md for detailed guidelines per step.
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.
Steps and saved files (all in output directory):
- Analyze →
01-analysis.md(domain, tone, terminology, translation challenges)
- Assemble prompt →
02-prompt.md(translation instructions with inlined context)
- Draft →
03-draft.md(initial translation with translator's notes; from subagent if chunked)
- Critical review →
04-critique.md(diagnosis only: accuracy, Europeanized language, strategy execution, expression issues)
- Revision →
05-revision.md(apply all critique findings to produce revised translation)
- Polish →
translation.md(final publication-quality translation)
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
Display 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 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.