Initial scaffold: Researcher Endorsement frontend

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

.github/skills/mock-data-generator/SKILL.md

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+---
+name: mock-data-generator
+description: "Generates robust mock datasets for papers, users, and endorsements so the frontend can function without a backend."
+license: MIT
+triggers:
+  - "generate mock data"
+  - "create mock papers"
+  - "seed mockData"
+---
+
+# 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.