# Mock Data Generator > Generates robust mock datasets for papers, users, and endorsements so the frontend can function without a backend. - Skill: `tomevault-io/mock-data-generator` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/mock-data-generator` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/mock-data-generator/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Web & Frontend - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/mock-data-generator --- # Mock Data Generator When to use this skill - Use early in development to simulate arXiv papers, users, and endorsement relations for UI and store integration. - Triggered by requests to create JSON or TypeScript fixtures under `src/data/mockData.ts`. Instructions 1. First Step: Produce realistic paper fixtures (title, authors, categories, abstract, submittedAt) and user fixtures (id, name, affiliation, expertiseAreas). 2. Second Step: Optionally seed persisted store on first load if no data exists, using the mock dataset to populate `usePaperStore` or similar. 3. Third Step: Provide utility functions to filter and paginate mock data to emulate real API behavior. Examples - `src/data/mockData.ts` exports `{ papers, users, endorsements }` and helper `seedMockData()`. Notes - Keep the dataset representative (vary categories, dates) so components (sorting, filtering) can be tested effectively. --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/cargdev) — claim your Tome and manage your conversions.