Skill by ara.so — Daily 2026 Skills collection.
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontranslate-book-parallelExecute the skills CLI command in your project's root directory to begin installation:
Fetches translate-book-parallel from aradotso/trending-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate translate-book-parallel. Access via /translate-book-parallel in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Skill by ara.so — Daily 2026 Skills collection.
A Claude Code skill that translates entire books (PDF/DOCX/EPUB) into any language using parallel subagents. Each chunk gets an isolated context window — preventing truncation and context accumulation that plague single-session translation.
Input (PDF/DOCX/EPUB)
│
▼
Calibre ebook-convert → HTMLZ → HTML → Markdown
│
▼
Split into chunks (~6000 chars each)
│ manifest.json tracks SHA-256 hashes
▼
Parallel subagents (8 concurrent by default)
│ each: read chunk → translate → write output_chunk*.md
▼
Validate (manifest hash check, 1:1 source↔output match)
│
▼
Merge → Pandoc → HTML (with TOC) → Calibre → DOCX / EPUB / PDF
# 1. Calibre (provides ebook-convert)
# macOS
brew install --cask calibre
# Linux
sudo apt-get install calibre
# Or download from https://calibre-ebook.com/
# 2. Pandoc
brew install pandoc # macOS
sudo apt-get install pandoc # Linux
# 3. Python dependencies
pip install pypandoc beautifulsoup4
Verify all tools are available:
ebook-convert --version
pandoc --version
python3 -c "import pypandoc; print('pypandoc ok')"
Option A: npx (recommended)
npx skills add deusyu/translate-book -a claude-code -g
Option B: ClawHub
clawhub install translate-book
Option C: Git clone
git clone https://github.com/deusyu/translate-book.git ~/.claude/skills/translate-book
Once the skill is installed, use natural language inside Claude Code:
translate /path/to/book.pdf to Chinese
translate ~/Downloads/mybook.epub to Japanese
/translate-book translate /path/to/book.docx to French
The skill orchestrates the full pipeline automatically.
| Code | Language |
|---|---|
zh |
Chinese |
en |
English |
ja |
Japanese |
ko |
Korean |
fr |
French |
de |
German |
es |
Spanish |
Language codes are extensible — add new ones in the skill definition.
python3 scripts/convert.py /path/to/book.pdf --olang zh
This produces inside {book_name}_temp/:
chunk0001.md, chunk0002.md, ... (source chunks, ~6000 chars each)manifest.json (SHA-256 hashes for validation)# For EPUB input
python3 scripts/convert.py /path/to/book.epub --olang ja
# For DOCX input
python3 scripts/convert.py /path/to/book.docx --olang fr
The skill handles this step — it launches 8 concurrent subagents per batch, each translating one chunk independently:
# Each subagent receives exactly this task:
Read chunk0042.md → translate to target language → write output_chunk0042.md
Resumable: Already-translated chunks (valid output_chunk*.md files) are skipped on re-run.
python3 scripts/merge_and_build.py \
--temp-dir book_name_temp \
--title "《Book Title in Target Language》"
Before merging, validation checks:
manifest.json (no stale outputs)Outputs produced:
| File | Description |
|---|---|
output.md |
Merged translated Markdown |
book.html |
Web version with floating TOC |
book.docx |
Word document |
book.epub |
E-book format |
book.pdf |
Print-ready PDF |
translate-book/
├── SKILL.md # Claude Code skill definition (orchestrator)
├── scripts/
│ ├── convert.py # PDF/DOCX/EPUB → Markdown chunks via Calibre HTMLZ
│ ├── manifest.py # SHA-256 chunk tracking and merge validation
│ ├── merge_and_build.py # Merge chunks → HTML → DOCX/EPUB/PDF
│ ├── calibre_html_publish.py # Calibre wrapper for format conversion
│ ├── template.html # Web HTML template with floating TOC
│ └── template_ebook.html # Ebook HTML template
└── README.md
# scripts/manifest.py (conceptual usage)
# During convert.py — records source hashes
manifest = {
"chunk0001.md": "sha256:abc123...",
"chunk0002.md": "sha256:def456...",
# ...
}
# During merge_and_build.py — validates before merging
# 1. Check every chunk has a corresponding output_chunk
# 2. Re-hash source chunks and compare against manifest
# 3. Reject if any hash mismatches (stale/corrupt output)
# 4. Reject if any output file is empty
If validation fails, the script auto-deletes stale output.md and re-merges from valid chunk outputs.
# 1. Install the skill
npx skills add deusyu/translate-book -a claude-code -g
# 2. Open Claude Code in your working directory
cd ~/books
# 3. Say in Claude Code:
# "translate clean-code.pdf to Chinese"
# Claude Code will:
# - Run convert.py to split into chunks
# - Launch 8 parallel subagents per batch
# - Each subagent translates one chunk
# - Validate all outputs via manifest
# - Merge and build all formats
# 4. Outputs appear in:
ls clean-code_temp/
# chunk0001.md chunk0002.md ... (source)
# output_chunk0001.md ... (translated)
# manifest.json
# output.md
# book.html
# book.docx
# book.epub
# book.pdf
# If translation is interrupted, just re-run the same command:
# "translate clean-code.pdf to Chinese"
# The skill detects existing output_chunk*.md files
# and skips already-translated chunks automatically.
# Only missing or failed chunks are retried.
If you need to update the title, author, template, or image assets without re-translating:
# Delete only the final artifacts (keeps translated chunks)
cd book_name_temp/
rm -f output.md book*.html book.docx book.epub book.pdf
# Re-run merge step
python3 ../scripts/merge_and_build.py \
--temp-dir . \
--title "《New Title》"
Do NOT delete chunk files — those are your translated content. Only delete final artifacts when changing metadata.
| Problem | Solution |
|---|---|
Calibre ebook-convert not found |
Install Calibre; ensure ebook-convert is in $PATH |
Manifest validation failed |
Source chunks changed — re-run convert.py |
Missing source chunk |
Source file deleted — re-run convert.py to regenerate |
| Incomplete translation | Re-run the skill — resumes from last valid chunk |
| Changed title/template but output unchanged | Delete output.md, book*.html, book.docx, book.epub, book.pdf then re-run merge_and_build.py |
output.md exists but manifest invalid |
Script auto-deletes stale output and re-merges |
| PDF generation fails | Verify Calibre has PDF output support; try ebook-convert --help |
| Empty output chunks | Retry failed chunks; check API rate limits |
# Check which chunks are missing translation
ls book_temp/chunk*.md | wc -l # total source chunks
ls book_temp/output_chunk*.md | wc -l # translated chunks so far
# Find missing output chunks
for f in book_temp/chunk*.md; do
base=$(basename "$f" .md)
out="book_temp/output_${base}.md"
if [ ! -f "$out" ] || [ ! -s "$out" ]; then
echo "Missing: $out"
fi
done
# Check manifest
cat book_temp/manifest.json | python3 -m json.tool | head -30
SKILL.md if hitting rate limits.SKILL.md.scripts/template.html and scripts/template_ebook.html for different HTML/ebook styling.Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
translate-book-parallel is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: translate-book-parallel is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: translate-book-parallel is focused, and the summary matches what you get after install.
Keeps context tight: translate-book-parallel is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend translate-book-parallel for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
translate-book-parallel has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for translate-book-parallel matched our evaluation — installs cleanly and behaves as described in the markdown.
translate-book-parallel fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
translate-book-parallel reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added translate-book-parallel from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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