--- name: speak-hello-world-7744378f41d8 description: | Create a minimal working Speak language learning example. Use when starting a new Speak integration, testing your setup, or learning basic Speak API patterns for language tutoring. Trigger with phrases like "speak hello world", "speak example", "speak quick start", "simple speak lesson". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore --- # Speak Hello World ## Overview Minimal working example demonstrating core Speak functionality for AI-powered language learning. ## Prerequisites - Completed `speak-install-auth` setup - Valid API credentials configured - Development environment ready - Microphone access for speech input (optional for testing) ## Instructions ### Step 1: Create Entry File Create a new file for your hello world lesson. ### Step 2: Import and Initialize Client ```typescript // src/speak-hello-world.ts import { SpeakClient, LessonSession, AITutor } from '@speak/language-sdk'; const client = new SpeakClient({ apiKey: process.env.SPEAK_API_KEY!, appId: process.env.SPEAK_APP_ID!, language: 'es', // Learning Spanish }); ``` ### Step 3: Create Your First Lesson Session ```typescript async function startFirstLesson() { // Initialize AI tutor const tutor = new AITutor(client, { targetLanguage: 'es', nativeLanguage: 'en', proficiencyLevel: 'beginner', }); // Start a conversation practice session const session = await tutor.startSession({ topic: 'greetings', duration: 5, // 5 minutes }); // Get AI tutor's opening prompt const opening = await session.getPrompt(); console.log('AI Tutor says:', opening.text); console.log('Audio URL:', opening.audioUrl); // Simulate user response (in production, use speech recognition) const feedback = await session.submitResponse({ text: 'Hola, me llamo Juan', audioData: null, // Optional: audio buffer for pronunciation scoring }); console.log('Feedback:', feedback.message); console.log('Pronunciation:', feedback.pronunciationScore); console.log('Grammar:', feedback.grammarCorrections); return session; } startFirstLesson().catch(console.error); ``` ### Step 4: Run Your First Lesson ```bash npx tsx src/speak-hello-world.ts ``` ## Output - Working code file with Speak client initialization - Successful lesson session creation - AI tutor prompt and feedback displayed - Console output showing: ``` AI Tutor says: Hola! Welcome to your Spanish lesson. Let's practice greetings. Can you say "Hello, my name is..." in Spanish? Audio URL: https://speak.com/audio/abc123.mp3 Feedback: Great job! Your pronunciation was clear. Pronunciation: 85 Grammar: [No corrections needed] ``` ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Import Error | SDK not installed | Verify with `npm list @speak/language-sdk` | | Auth Error | Invalid credentials | Check environment variables are set | | Session Timeout | Exceeded lesson duration | Extend session or start new one | | Rate Limit | Too many requests | Wait and retry with exponential backoff | | Language Not Supported | Invalid language code | Use supported language codes | ## Examples ### TypeScript: Pronunciation Practice ```typescript import { SpeakClient, PronunciationPractice } from '@speak/language-sdk'; const client = new SpeakClient({ apiKey: process.env.SPEAK_API_KEY!, appId: process.env.SPEAK_APP_ID!, language: 'ko', }); async function practicePronunciation() { const practice = new PronunciationPractice(client); // Get a phrase to practice const phrase = await practice.getPhrase({ difficulty: 'easy', category: 'daily_conversation', }); console.log('Practice this phrase:'); console.log('Korean:', phrase.text); console.log('Romanization:', phrase.romanization); console.log('English:', phrase.translation); console.log('Listen:', phrase.audioUrl); } practicePronunciation(); ``` ### Python: Basic Lesson ```python from speak_sdk import SpeakClient, AITutor client = SpeakClient( api_key=os.environ.get('SPEAK_API_KEY'), app_id=os.environ.get('SPEAK_APP_ID'), language='ja' ) async def first_lesson(): tutor = AITutor(client, target_language='ja', native_language='en') session = await tutor.start_session(topic='self_introduction') prompt = await session.get_prompt() print(f"Tutor: {prompt.text}") # Submit response feedback = await session.submit_response(text="Hajimemashite, watashi wa John desu") print(f"Feedback: {feedback.message}") asyncio.run(first_lesson()) ``` ### Vocabulary Quiz Example ```typescript async function vocabularyQuiz() { const quiz = await client.vocabulary.createQuiz({ language: 'es', topic: 'food', questionCount: 5, type: 'multiple_choice', }); for (const question of quiz.questions) { console.log(`Q: ${question.prompt}`); console.log(`Options: ${question.options.join(', ')}`); // In production, get user input const answer = await quiz.submitAnswer(question.id, 'answer_a'); console.log(`Correct: ${answer.correct}`); } console.log(`Final Score: ${quiz.score}/${quiz.total}`); } ``` ## Resources - [Speak Getting Started](https://developer.speak.com/docs/getting-started) - [Speak API Reference](https://developer.speak.com/api) - [Speak Lesson Types](https://developer.speak.com/docs/lesson-types) - [Speech Recognition Guide](https://developer.speak.com/docs/speech-recognition) ## Next Steps Proceed to `speak-local-dev-loop` for development workflow setup. --- Source attribution: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/speak-pack/skills/speak-hello-world/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License (with OpenAI/Anthropic Rider) Copyright (c) 2026 Jeffrey Emanuel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: ADDITIONAL RIDER / RESTRICTION (OpenAI / Anthropic): This rider is part of the "conditions" of this License. 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Any breach of this rider automatically and immediately terminates the permissions granted by this License. Upon termination, you must immediately cease all use and distribution of the Software and any Derivative Works and destroy all copies under your control. You agree that a breach of this rider would cause irreparable harm and that Jeffrey Emanuel may seek injunctive or other equitable relief to enforce this rider, in addition to any other remedies available at law. To the maximum extent permitted by applicable law, the prevailing party in any action to enforce this rider shall be entitled to recover reasonable attorneys' fees and costs. For purposes of this rider, "Affiliate" means any entity that directly or indirectly controls, is controlled by, or is under common control with the specified party. "Control" means ownership of more than 50% of the voting securities or other ownership interest, or the power to direct management or policies by contract or otherwise. 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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/speak-pack/skills/speak-hello-world/SKILL.md Attribution basis: Source repository record Fields of work: Design, Education & Research, Marketing Roles: Content Marketer, Tutor / Instructor, UX Designer Specialties: API Tools: @Speak/Language Sdk Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 3529163da8786dc46a7501b59436fe1987e478788f0c10c86440990e9fe45da6