Agent skill

Baoyu Translate

by LeoYeAI in LeoYeAI/openclaw-master-skills

Translates articles and documents between languages with three modes - quick (direct), normal (analyze then translate), and refined (analyze, translate, review, polish).

MITAuto-check passedWriting & Content

Install Baoyu Translate

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-translate -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills baoyu-translate --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/baoyu-translate .claude/skills/baoyu-translate && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
baoyu-translate
GitHub stars
2.2k
Token cost
~4.6k tokens
SKILL.md length
1,925 words
Files
12 (incl. scripts, references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

Translates articles and documents between languages with three modes - quick (direct), normal (analyze then translate), and refined (analyze, translate, review, polish).

  • Works in 5 steps: Load Preferences → Materialize Source & Create Output… → Assess Content Length → …
  • User asks to translate
  • SKILL.md covers Script Directory, Preferences (EXTEND.md), Defaults and Modes, plus 3 more sections
  • Runs TypeScript scripts from its folder; calls npx

What it does

Baoyu Translate is an agent skill from LeoYeAI/openclaw-master-skills. 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"…

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 14 other files, including scripts and reference files (for example `_meta.json`, `references/config/extend-schema.md` and `references/config/first-time-setup.md`).

It sits in Writing & Content, covering Translation and Copy editing and proofreading. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • User asks to translate
  • Translate article
  • Translate to Chinese/English
  • Convert to Chinese

Example prompts

  • “translate”
  • “translate article”
  • “translate to Chinese/English”
  • “/baoyu-translate”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Load Preferences
  2. Materialize Source & Create Output Directory
  3. Assess Content Length
  4. Translate & Refine
  5. Output

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Baoyu Translate loads about 4.6k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 152 tokens; SKILL.md has 1,925 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~152
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,925 words, ~4,633 tokens.

Download SKILL.mdSave it as .claude/skills/baoyu-translate/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
baoyu-translate
description
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", "快翻", "这篇文章翻译一下", or when a URL or file is provided with translation intent.
version
1.57.0

Translator

Three-mode translation skill: quick for direct translation, normal for analysis-informed translation, refined for full publication-quality workflow with review and polish.

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.

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

Preferences (EXTEND.md)

Check EXTEND.md existence (priority order):

bash
# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-translate/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-translate/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-translate/EXTEND.md" && echo "user"
powershell
# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-translate/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-translate/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-translate/EXTEND.md") { "user" }
PathLocation
.baoyu-skills/baoyu-translate/EXTEND.mdProject directory
$HOME/.baoyu-skills/baoyu-translate/EXTEND.mdUser home
ResultAction
FoundRead, parse, apply settings. On first use in session, briefly remind: "Using preferences from [path]. You can edit EXTEND.md to customize glossary, audience, etc."
Not foundMUST 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.

SettingDefaultEXTEND.md keyCLI flagDescription
Target languagezh-CNtarget_language--toTranslation target language
Modenormaldefault_mode--modeTranslation mode
Audiencegeneralaudience--audienceTarget reader profile
Stylestorytellingstyle--styleTranslation style preference
Chunk threshold4000chunk_threshold—Word count to trigger chunked translation
Chunk max words5000chunk_max_words—Max words per chunk

Modes

ModeFlagStepsWhen to Use
Quick--mode quickTranslateShort texts, informal content, quick tasks
Normal--mode normal (default)Analyze → TranslateArticles, blog posts, general content
Refined--mode refinedAnalyze → Translate → Review → PolishPublication-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):

ValueDescriptionEffect
storytellingEngaging narrative flow (default)Draws readers in, smooth transitions, vivid phrasing
formalProfessional, structuredNeutral tone, clear organization, no colloquialisms
technicalPrecise, documentation-styleConcise, terminology-heavy, minimal embellishment
literalClose to original structureMinimal restructuring, preserves source sentence patterns
academicScholarly, rigorousFormal register, complex clauses OK, citation-aware
businessConcise, results-focusedAction-oriented, executive-friendly, bullet-point mindset
humorousPreserves and adapts humorWitty, playful, recreates comedic effect in target language
conversationalCasual, spoken-likeFriendly, approachable, as if explaining to a friend
elegantLiterary, polished proseAesthetically 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.

Usage

/translate [--mode quick|normal|refined] [--from <lang>] [--to <lang>] [--audience <audience>] [--style <style>] [--glossary <file>] <source>
  • <source>: File path, URL, or inline text
  • --from: Source language (auto-detect if omitted)
  • --to: Target language (from EXTEND.md or default zh-CN)
  • --audience: Target reader profile (from EXTEND.md or default general)
  • --style: Translation style (from EXTEND.md or default storytelling)
  • --glossary: Additional glossary file to merge with EXTEND.md glossary

Audience presets:

ValueDescriptionEffect
generalGeneral readers (default)Plain language, more translator's notes for jargon
technicalDevelopers / engineersLess annotation on common tech terms
academicResearchers / scholarsFormal register, precise terminology
businessBusiness professionalsBusiness-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:

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):

FileModeDescription
translation.mdAllFinal translation (always this name)
01-analysis.mdNormal, RefinedContent analysis (domain, tone, terminology)
02-prompt.mdNormal, RefinedAssembled translation prompt
03-draft.mdRefinedInitial draft before review
04-critique.mdRefinedCritical review findings (diagnosis only)
05-revision.mdRefinedRevised translation based on critique
chunks/ChunkedSource 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:

ContentAction
< chunk thresholdTranslate as single unit
>= chunk thresholdChunk translation (see Step 3.1)

3.1 Long Content Preparation (normal/refined modes, >= chunk threshold only)

Before translating chunks:

  1. Extract terminology: Scan entire document for proper nouns, technical terms, recurring phrases
  2. Build session glossary: Merge extracted terms with loaded glossaries, establish consistent translations
  3. 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
  4. 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 + source voice assessment, content background, merged glossary, figurative language mapping (structured table), comprehension challenges (with reasoning), and translation challenges (structural/creative)
    • Save as 02-prompt.md in the output directory (shared context only, no task instructions)
  5. 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
  6. 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)
  7. 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).

Show full SKILL.md (816 more words)Show less
Step 4: Translate & Refine

Translation principles (apply to all modes):

  • Accuracy first: Facts, data, and logic must match the original exactly
  • Meaning over words: Translate what the author means, not just what the words say. When a literal translation sounds unnatural or fails to convey the intended effect, restructure freely to express the same meaning in idiomatic target language
  • Figurative language: Interpret metaphors, idioms, and figurative expressions by their intended meaning rather than translating them word-for-word. When a source-language image does not carry the same connotation in the target language, replace it with a natural expression that conveys the same idea and emotional effect
  • Emotional fidelity: Preserve the emotional connotations of word choices, not just their dictionary meanings. Words that carry subjective feelings (e.g., "alarming", "haunting") should be rendered to evoke the same response in target-language readers
  • Natural flow: Use idiomatic target language word order and sentence patterns; break or restructure sentences freely when the source structure doesn't work naturally in the target language
  • Terminology: Use standard translations; annotate with original term in parentheses on first occurrence
  • Preserve format: Keep all markdown formatting (headings, bold, italic, images, links, code blocks)
  • Image-language awareness: Preserve image references exactly during translation, but after the translation is complete, review referenced images and check whether their likely main text language still matches the translated article language
  • Frontmatter transformation: If the source has YAML frontmatter, preserve it in the translation with these changes: (1) Rename metadata fields that describe the source article — url→sourceUrl, title→sourceTitle, description→sourceDescription, author→sourceAuthor, date→sourceDate, and any similar origin-metadata fields — by adding a source prefix (camelCase). (2) Translate the values of text fields (title, description, etc.) and add them as new top-level fields. (3) Keep other fields (tags, categories, custom fields) as-is, translating their values where appropriate
  • Respect original: Maintain original meaning and intent; do not add, remove, or editorialize — but sentence structure and imagery may be adapted freely to serve the meaning
  • Translator's notes: For terms, concepts, or cultural references that target readers may not understand — due to jargon, cultural gaps, or domain-specific knowledge — add a concise explanatory note in parentheses immediately after the term. The note should explain what it means in plain language, not just provide the English original. Format: 译文(English original,通俗解释). Calibrate annotation depth to the target audience: general readers need more notes than technical readers. For short texts (< 5 sentences), further reduce annotations — only annotate non-common terms that the target audience is unlikely to know; skip terms that are widely recognized or self-explanatory in context. Only add notes where genuinely needed; do not over-annotate obvious terms.
Quick Mode

Translate directly → save to translation.md. No analysis file, but still apply all translation principles above — especially: interpret figurative language by meaning (not word-for-word), preserve emotional connotations, and restructure sentences for natural target-language flow.

Normal Mode
  1. Analyze → 01-analysis.md (domain, tone, audience, terminology, reader comprehension challenges, figurative language & metaphor mapping)
  2. Assemble prompt → 02-prompt.md (translation instructions with inlined style preset, content background, glossary, and comprehension challenges)
  3. 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):

  1. Analyze → 01-analysis.md (domain, tone, terminology, reader comprehension challenges, figurative language & metaphor mapping)
  2. Assemble prompt → 02-prompt.md (translation instructions with inlined context)
  3. Draft → 03-draft.md (initial translation with translator's notes; from subagent 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 to produce revised translation)
  6. 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:

  1. Collect image references from the translated article
  2. Identify likely text-heavy images such as covers, screenshots, diagrams, charts, frameworks, and infographics
  3. If any image likely contains a main text language that does not match the translated article language, proactively remind the user
  4. 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):

text
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

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.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (scripts, references) in skills/baoyu-translate of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/config/extend-schema.md
  • references/config/first-time-setup.md
  • references/glossary-en-zh.md
  • references/refined-workflow.md
  • references/subagent-prompt-template.md
  • references/workflow-mechanics.md
  • scripts/bun.lock
  • scripts/chunk.ts
  • scripts/main.ts
  • scripts/package.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Baoyu Translate next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Baoyu Translate compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Baoyu Translate this skillLeoYeAI/openclaw-master-skills2.2k—~4.6kAutomated safety check: PassMIT
Baoyu TranslateJimLiu/baoyu-skills27k1 repos~3.9kAutomated safety check: PassMIT
Academic Prose De-AI Editorheise3/academic-deai254—~1.4kAutomated safety check: PassMIT
Chinese Documentation Style GuidejnMetaCode/superpowers-zh8.3k—~1.6kAutomated safety check: PassMIT
Academic Paper PolishHKUSTDial/Supervisor-Skills8.8k—~3.1kAutomated safety check: PassCC-BY-NC-SA-4.0
Nature-Style Academic PolishingYuan1z0825/nature-skills47k—~1.5kAutomated safety check: PassApache-2.0

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Questions about Baoyu Translate

What does Baoyu Translate do?

Translates articles and documents between languages with three modes - quick (direct), normal (analyze then translate), and refined (analyze, translate, review, polish). Baoyu Translate is an agent skill from LeoYeAI/openclaw-master-skills. Translates articles and documents between languages with three modes - quick (direct), normal (analyze then translate), and refined (analyze, translate, review, polish).

When should I use Baoyu Translate?

Baoyu Translate fits situations like: user asks to translate; translate article; translate to Chinese/English; convert to Chinese.

How do I install Baoyu Translate in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-translate -a claude-code`. Or copy the skill folder (skills/baoyu-translate in LeoYeAI/openclaw-master-skills) into .claude/skills/baoyu-translate in your project. Claude Code loads it when a task matches its description.

How do I install Baoyu Translate in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-translate -a codex`. Or copy the skill folder (skills/baoyu-translate in LeoYeAI/openclaw-master-skills) into .agents/skills/baoyu-translate in your project. Codex loads it when a task matches its description.

Can I use Baoyu Translate in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-translate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/baoyu-translate, .gemini/skills/baoyu-translate, .github/skills/baoyu-translate and .opencode/skills/baoyu-translate in your project.

What does Baoyu Translate need to run?

Going by SKILL.md and its folder, Baoyu Translate needs TypeScript for the scripts in its folder and the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Baoyu Translate access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Baoyu Translate safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Baoyu Translate use?

Baoyu Translate is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Baoyu Translate use?

About 4.6k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.6k tokens, read only when the agent opens those files.

What are the alternatives to Baoyu Translate?

Skills that share tags, products or a category with Baoyu Translate: Baoyu Translate (JimLiu/baoyu-skills, 27k stars), Academic Prose De-AI Editor (heise3/academic-deai, 254 stars), Chinese Documentation Style Guide (jnMetaCode/superpowers-zh, 8.3k stars) and Academic Paper Polish (HKUSTDial/Supervisor-Skills, 8.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Baoyu Translate?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.