--- name: twinmind-local-dev-loop-1acbdeeb0f62 description: | Set up local development workflow with TwinMind API integration. Use when building applications that integrate TwinMind transcription, testing API calls locally, or developing meeting automation tools. Trigger with phrases like "twinmind dev setup", "twinmind local development", "twinmind API testing", "build with twinmind". allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(pip:*), Bash(curl:*) version: 1.0.0 license: MIT author: Jeremy Longshore --- # TwinMind Local Dev Loop ## Overview Configure a productive local development environment for TwinMind API integration. ## Prerequisites - TwinMind Pro or Enterprise account (API access) - Node.js 18+ or Python 3.10+ - API key from TwinMind dashboard - Local development environment ## Instructions ### Step 1: Project Setup ```bash # Create project directory mkdir twinmind-integration && cd twinmind-integration # Initialize Node.js project npm init -y # Install dependencies npm install dotenv axios zod typescript ts-node @types/node # Initialize TypeScript npx tsc --init ``` ### Step 2: Configure Environment ```bash # Create environment file cat > .env << 'EOF' TWINMIND_API_KEY=your-api-key-here TWINMIND_API_URL=https://api.twinmind.com/v1 TWINMIND_WEBHOOK_SECRET=your-webhook-secret NODE_ENV=development EOF # Add to .gitignore echo ".env" >> .gitignore echo "node_modules" >> .gitignore ``` ### Step 3: Create TwinMind Client ```typescript // src/twinmind/client.ts import axios, { AxiosInstance } from 'axios'; import { z } from 'zod'; // Response schemas const TranscriptSchema = z.object({ id: z.string(), text: z.string(), duration_seconds: z.number(), language: z.string(), speakers: z.array(z.object({ id: z.string(), name: z.string().optional(), segments: z.array(z.object({ start: z.number(), end: z.number(), text: z.string(), confidence: z.number(), })), })), created_at: z.string(), }); const SummarySchema = z.object({ id: z.string(), transcript_id: z.string(), summary: z.string(), action_items: z.array(z.object({ text: z.string(), assignee: z.string().optional(), due_date: z.string().optional(), })), key_points: z.array(z.string()), }); export type Transcript = z.infer; export type Summary = z.infer; export class TwinMindClient { private client: AxiosInstance; constructor(apiKey: string, baseUrl?: string) { this.client = axios.create({ baseURL: baseUrl || 'https://api.twinmind.com/v1', headers: { 'Authorization': `Bearer ${apiKey}`, 'Content-Type': 'application/json', }, timeout: 30000, }); } async healthCheck(): Promise { const response = await this.client.get('/health'); return response.status === 200; } async transcribe(audioUrl: string, options?: { language?: string; diarization?: boolean; model?: 'ear-3' | 'ear-2'; }): Promise { const response = await this.client.post('/transcribe', { audio_url: audioUrl, language: options?.language || 'auto', diarization: options?.diarization ?? true, model: options?.model || 'ear-3', }); return TranscriptSchema.parse(response.data); } async summarize(transcriptId: string): Promise { const response = await this.client.post('/summarize', { transcript_id: transcriptId, }); return SummarySchema.parse(response.data); } async search(query: string, options?: { limit?: number; date_from?: string; date_to?: string; }): Promise { const response = await this.client.get('/search', { params: { q: query, limit: options?.limit || 10, date_from: options?.date_from, date_to: options?.date_to, }, }); return z.array(TranscriptSchema).parse(response.data.results); } } ``` ### Step 4: Create Dev Runner Script ```typescript // src/dev.ts import 'dotenv/config'; import { TwinMindClient } from './twinmind/client'; async function main() { const client = new TwinMindClient(process.env.TWINMIND_API_KEY!); // Health check console.log('Checking TwinMind API health...'); const healthy = await client.healthCheck(); console.log(`API Status: ${healthy ? 'Healthy' : 'Unhealthy'}`); // Example: Transcribe audio file // const transcript = await client.transcribe('https://example.com/meeting.mp3'); // console.log('Transcript:', transcript); // Example: Generate summary // const summary = await client.summarize(transcript.id); // console.log('Summary:', summary); // Example: Search memory vault // const results = await client.search('budget review'); // console.log('Search results:', results); } main().catch(console.error); ``` ### Step 5: Configure Dev Scripts ```json // package.json scripts { "scripts": { "dev": "ts-node src/dev.ts", "build": "tsc", "test": "jest", "lint": "eslint src/**/*.ts", "typecheck": "tsc --noEmit" } } ``` ### Step 6: Create Test Fixtures ```typescript // tests/fixtures/mock-responses.ts export const mockTranscript = { id: 'tr_test_123', text: 'Welcome to the meeting. Today we discuss the project timeline.', duration_seconds: 45, language: 'en', speakers: [ { id: 'spk_1', name: 'Host', segments: [ { start: 0, end: 5.2, text: 'Welcome to the meeting.', confidence: 0.97, }, { start: 5.5, end: 12.1, text: 'Today we discuss the project timeline.', confidence: 0.95, }, ], }, ], created_at: '2025-01-15T10:00:00Z', }; export const mockSummary = { id: 'sum_test_456', transcript_id: 'tr_test_123', summary: 'Brief meeting to discuss project timeline and milestones.', action_items: [ { text: 'Review timeline document', assignee: 'John', due_date: '2025-01-20', }, ], key_points: [ 'Project kickoff confirmed', 'Timeline review scheduled', ], }; ``` ### Step 7: Run Development Loop ```bash # Start development npm run dev # Watch mode (requires nodemon) npm install -D nodemon npx nodemon --exec ts-node src/dev.ts # Run with debug logging DEBUG=twinmind:* npm run dev ``` ## Output - Project structure with TypeScript configuration - TwinMind client with type-safe schemas - Environment configuration - Development scripts - Test fixtures for offline development ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | API key missing | .env not loaded | Check dotenv import | | Connection refused | Wrong API URL | Verify TWINMIND_API_URL | | Rate limited | Too many requests | Add delay between calls | | Schema validation failed | API response changed | Update Zod schemas | | Timeout | Large audio file | Increase timeout value | ## Project Structure ``` twinmind-integration/ ├── src/ │ ├── twinmind/ │ │ ├── client.ts # API client │ │ ├── types.ts # TypeScript types │ │ └── errors.ts # Error classes │ ├── services/ │ │ └── meeting.ts # Business logic │ └── dev.ts # Development entry ├── tests/ │ ├── fixtures/ │ │ └── mock-responses.ts │ └── twinmind.test.ts ├── .env # Environment (gitignored) ├── .env.example # Template ├── package.json └── tsconfig.json ``` ## Resources - [TwinMind API Documentation](https://twinmind.com/docs/api) - [Ear-3 Model Specification](https://twinmind.com/ear-3) - [Zod Documentation](https://zod.dev/) ## Next Steps Apply patterns in `twinmind-sdk-patterns` for production-ready code. --- Source attribution: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/twinmind-pack/skills/twinmind-local-dev-loop/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Dave AI. ## 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. # Dave AI 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/twinmind-pack/skills/twinmind-local-dev-loop/SKILL.md Attribution basis: Source repository record Fields of work: Development & Engineering, Product Management Roles: Backend Developer, Growth Product Manager, Product Manager Specialties: Backend Tools: Twinmind Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: ab1b5ce4447a36938349f633064a371641f44190eaebc201ab6ef1e9c13de395