book-translation▌
f/prompts.chat · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Translate \"The Interactive Book of Prompting\" chapters and UI strings to a new language.
- ›Covers 25 chapters across 7 parts, requiring translation of MDX content files and JSON UI strings in a specified locale directory structure
- ›Recommends copying the complete Turkish translation as a base rather than translating from English, preserving all JSX components and Markdown syntax while translating prose only
- ›Requires registration of new locale in src/components/book/elements/locales/in
Book Translation Skill
This skill guides translation of book content for The Interactive Book of Prompting at prompts.chat.
Overview
The book has 25 chapters across 7 parts. Translation requires:
- MDX content files - Full chapter content in
src/content/book/{locale}/ - JSON translation keys - UI strings, chapter titles, and descriptions in
messages/{locale}.json
Prerequisites
Before starting, identify:
- Target locale code (e.g.,
de,fr,es,ja,ko,zh) - Check if locale exists in
messages/directory - Check if
src/content/book/{locale}/folder exists
Step 1: Copy Turkish Folder as Base
The Turkish (tr) translation is complete and well-tested. Copy it as your starting point instead of translating from English:
mkdir -p src/content/book/{locale}
cp -r src/content/book/*.mdx src/content/book/{locale}/
cp src/components/book/elements/locales/en.ts src/components/book/elements/locales/{locale}.ts
⚠️ IMPORTANT: After copying, you MUST register the new locale in src/components/book/elements/locales/index.ts:
- Add import:
import {locale} from "./{locale}"; - Add to
localesobject:{locale}, - Add to named exports:
export { en, tr, az, {locale} };
This is faster because:
- Turkish and many languages share similar sentence structures
- All JSX/React components are already preserved correctly
- File structure is already set up
- You only need to translate the prose, not recreate the structure
Step 2: Translate MDX Content Files
Edit each copied file in src/content/book/{locale}/ to translate from Turkish to your target language.
Process files one by one:
Chapter List (in order)
| Slug | English Title |
|---|---|
00a-preface |
Preface |
00b-history |
History |
00c-introduction |
Introduction |
01-understanding-ai-models |
Understanding AI Models |
02-anatomy-of-effective-prompt |
Anatomy of an Effective Prompt |
03-core-prompting-principles |
Core Prompting Principles |
04-role-based-prompting |
Role-Based Prompting |
05-structured-output |
Structured Output |
06-chain-of-thought |
Chain of Thought |
07-few-shot-learning |
Few-Shot Learning |
08-iterative-refinement |
Iterative Refinement |
09-json-yaml-prompting |
JSON & YAML Prompting |
10-system-prompts-personas |
System Prompts & Personas |
11-prompt-chaining |
Prompt Chaining |
12-handling-edge-cases |
Handling Edge Cases |
13-multimodal-prompting |
Multimodal Prompting |
14-context-engineering |
Context Engineering |
15-common-pitfalls |
Common Pitfalls |
16-ethics-responsible-use |
Ethics & Responsible Use |
17-prompt-optimization |
Prompt Optimization |
18-writing-content |
Writing & Content |
19-programming-development |
Programming & Development |
20-education-learning |
Education & Learning |
21-business-productivity |
Business & Productivity |
22-creative-arts |
Creative Arts |
23-research-analysis |
Research & Analysis |
24-future-of-prompting |
The Future of Prompting |
25-agents-and-skills |
Agents & Skills |
MDX Translation Guidelines
- Preserve all JSX/React components - Keep
<div>,<img>,className, etc. unchanged - Preserve code blocks - Code examples should remain in English (variable names, keywords)
- Translate prose content - Headings, paragraphs, lists
- Keep Markdown syntax -
##,**bold**,*italic*,[links](url) - Preserve component imports - Any
importstatements at the top
Step 3: Translate JSON Keys
In messages/{locale}.json, translate the "book" section. Key areas:
Book Metadata
"book": {
"title": "The Interactive Book of Prompting",
"subtitle": "An Interactive Guide to Crafting Clear and Effective Prompts",
"metaTitle": "...",
"metaDescription": "...",
...
}
Chapter Titles (book.chapters)
"chapters": {
"00a-preface": "Preface",
"00b-history": "History",
"00c-introduction": "Introduction",
...
}
Chapter Descriptions (book.chapterDescriptions)
"chapterDescriptions": {
"00a-preface": "A personal note from the author",
"00b-history": "The story of Awesome ChatGPT Prompts",
...
}
Part Names (book.parts)
"parts": {
"introduction": "Introduction",
"foundations": "Foundations",
"techniques": "Techniques",
"advanced": "Advanced Strategies",
"bestPractices": "Best Practices",
"useCases": "Use Cases",
"conclusion": "Conclusion"
}
Interactive Demo Examples (book.interactive.demoExamples)
Localize example text for demos (tokenizer samples, temperature examples, etc.):
"demoExamples": {
"tokenPrediction": {
"tokens": ["The", " capital", " of", " France", " is", " Paris", "."],
"fullText": "The capital of France is Paris."
},
"temperature": {
"prompt": "What is the capital of France?",
...
}
}
Book Elements Locales (REQUIRED)
⚠️ DO NOT SKIP THIS STEP - The interactive demos will not work in the new language without this.
Translate the locale data file at src/components/book/elements/locales/{locale}.ts:
- Temperature examples, token predictions, embedding words
- Capabilities list, sample conversations, strategies
- Tokenizer samples, builder fields, chain types
- Frameworks (CRISPE, BREAK, RTF), exercises
- Image/video prompt options, validation demos
Then register it in src/components/book/elements/locales/index.ts:
import {locale} from "./{locale}";
const locales: Record<string, LocaleData> = {
en,
tr,
az,
{locale}, // Add your new locale here
};
export { en, tr, az, {locale} }; // Add to exports
UI Strings (book.interactive.*, book.chapter.*, book.search.*)
Translate all interactive component labels and navigation strings.
Step 4: Verify Translation
-
Run the check script:
node scripts/check-translations.js -
Start dev server and test:
npm run dev -
Navigate to
/bookwith the target locale to verify content loads
Reference: English Translation
The English (en) translation is complete and serves as the base template for all new translations:
- MDX files:
src/content/book/*.mdx— copy this files tosrc/content/book/{locale}/*.mdx - JSON keys:
messages/en.json→booksection — use as reference for structure
Recommended Workflow
- Copy
src/content/book/*.mdxtosrc/content/book/{locale}/*.mdx - Copy the
"book"section frommessages/en.jsontomessages/{locale}.json. Translate these in multiple agentic session instead of single time (token limit may exceed at once) - Edit each file, translating English → target language
- Keep all JSX components, code blocks, and Markdown syntax intact
Quality Guidelines
- Consistency: Use consistent terminology throughout (e.g., always translate "prompt" the same way)
- Technical terms: Some terms like "AI", "ChatGPT", "API" may stay in English
- Cultural adaptation: Adapt examples to be relevant for the target audience where appropriate
- Natural language: Prioritize natural-sounding translations over literal ones
How to use book-translation on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add book-translation
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches book-translation from GitHub repository f/prompts.chat and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate book-translation. Access the skill through slash commands (e.g., /book-translation) or your agent's skill management interface.
Security & Verification Notice
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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★25 reviews- ★★★★★Kabir Anderson· Dec 24, 2024
Solid pick for teams standardizing on skills: book-translation is focused, and the summary matches what you get after install.
- ★★★★★Sakshi Patil· Dec 12, 2024
I recommend book-translation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Kabir Gonzalez· Nov 15, 2024
book-translation has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Chaitanya Patil· Nov 3, 2024
Useful defaults in book-translation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Omar Choi· Nov 3, 2024
Keeps context tight: book-translation is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Piyush G· Oct 22, 2024
book-translation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ishan Khanna· Oct 6, 2024
Keeps context tight: book-translation is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Shikha Mishra· Sep 1, 2024
Keeps context tight: book-translation is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Emma Menon· Sep 1, 2024
Useful defaults in book-translation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Rahul Santra· Aug 20, 2024
book-translation has been reliable in day-to-day use. Documentation quality is above average for community skills.
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