# [FEATURE] Advanced Analytics Dashboard in TUI Showing Wallet Usage Patterns and Risk Alerts
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## 🚀 Problem Statement
The current `svmai` CLI provides robust wallet management and vanity wallet generation but lacks advanced analytics capabilities. Users have minimal visibility into their wallet usage patterns and associated risk factors, which limits their ability to make informed security decisions. This feature aims to deliver a comprehensive, **text-based analytics dashboard** within the TUI that surfaces wallet usage insights and real-time risk alerts.
By empowering users with actionable data and timely security warnings, we increase user trust, retention, and overall security hygiene — critical for a crypto wallet management tool.
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## 🧠 Technical Context
- **Repository:** `larp0/svmai-cli`
- **Language:** Rust
- **Current State:** Early MVP with basic wallet generation and scanning functionality.
- **Existing UI:** Text-based UI (TUI) implemented in Rust.
- **Security Focus:** Managing private keys securely using OS keychains.
- **User Impact:** Medium priority feature enhancing user insight.
- **Dependencies:** Potential use of Rust crates for analytics, TUI (e.g., `tui-rs`), async data fetching, and risk evaluation.
The feature fits into the broader AI Development Plan Milestone #2 and aligns with the project's goals to enhance innovation and user security awareness.
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## 🛠️ Implementation Steps
### 1. Research & Requirements Gathering
- Analyze market competitors and popular wallet analytics dashboards.
- Engage with target users or analyze existing feedback to understand desired metrics and alerts.
- Define a clear list of wallet usage patterns to monitor (e.g., transaction frequency, token balances, unusual activity).
- Define risk alert criteria (e.g., sudden large transfers, interaction with suspicious addresses).
### 2. Design UX & Technical Architecture
- Wireframe TUI dashboard layout showing key analytics panels, alert sections, and navigation.
- Define data flow: how wallet data will be collected, processed, and visualized.
- Plan modular Rust components for data aggregation, risk evaluation, and TUI rendering.
- Choose or design data structures optimized for performance and async updates.
### 3. Develop Analytics Data Layer
- Implement wallet usage data collectors: transaction history parsers, balance trackers.
- Implement risk alert logic based on configurable thresholds.
- Store analytics state efficiently, supporting incremental updates.
### 4. Implement TUI Dashboard Components
- Using the existing TUI framework, build UI components:
- Summary panel (wallet balances, transaction count)
- Usage patterns graphs or tables (e.g., daily transaction volume)
- Risk alerts panel with clear severity indicators
- Navigation and refresh controls
### 5. MVP Integration & Testing
- Integrate analytics data layer with TUI components.
- Ensure smooth updates and responsive user experience.
- Add command(s) or menu entries to access the dashboard.
- Write unit and integration tests for analytics logic and UI rendering.
- Perform manual exploratory testing with sample wallets.
### 6. User Feedback & Iteration
- Release the MVP feature to a limited audience or internal testers.
- Collect feedback on usability, clarity, and usefulness of analytics.
- Iterate on UI/UX and risk detection rules accordingly.
### 7. Documentation & Release Preparation
- Update README with feature overview and usage instructions.
- Document analytics metrics and risk alert definitions.
- Add code comments and developer documentation for maintainability.
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## 📐 Technical Specifications
| Aspect | Specification |
|-------------------------|------------------------------------------------------------------------------------------------|
| Language | Rust |
| TUI Framework | Existing TUI (likely `tui-rs` or similar) |
| Data Sources | Local wallet transaction history, balance info, possibly RPC calls to Solana nodes |
| Risk Alerts | Configurable rules (e.g., unusual transaction size, frequency, suspicious addresses) |
| State Management | Efficient in-memory state with support for incremental updates and caching |
| Performance | Low overhead, non-blocking UI updates, async data fetching |
| User Interaction | Keyboard-driven navigation, refresh keybinding, alert acknowledgement |
| Testing | Unit tests for analytics computations and risk rules; UI tests for dashboard rendering |
| Security | No sensitive data logging; respect private key security and OS keychain access constraints |
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## ✅ Acceptance Criteria
- [ ] Comprehensive feature requirements documented and approved.
- [ ] Technical design artifacts (wireframes, architecture diagrams) completed.
- [ ] Wallet usage data collection implemented accurately.
- [ ] Risk alert system implemented with at least 3 distinct alert types.
- [ ] Interactive TUI dashboard fully integrated and accessible via CLI commands.
- [ ] Unit and integration tests covering >80% of new code.
- [ ] Manual and automated testing confirms no regressions or crashes.
- [ ] User feedback collected from at least 3 testers and documented.
- [ ] Documentation updated with detailed usage instructions and developer notes.
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## 🧪 Testing Requirements
- **Unit Testing:** Analytics calculations, risk logic, and data parsers.
- **Integration Testing:** End-to-end flow from wallet data extraction to TUI rendering.
- **UI Testing:** Keyboard navigation, dashboard refresh, alert display correctness.
- **Security Testing:** Verify no sensitive key material leaks in logs or UI.
- **Performance Testing:** Ensure dashboard updates smoothly even with large wallet histories.
- **User Acceptance Testing:** Gather feedback on feature clarity and utility.
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## 📚 Documentation Needs
- Update `README.md` with new feature overview and CLI usage docs.
- Add a new docs page `/docs/analytics-dashboard.md` detailing:
- Metrics tracked and their meanings.
- Risk alert explanations and configuration.
- Troubleshooting common issues.
- Inline code comments explaining complex logic.
- Changelog entry describing the new analytics dashboard feature.
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## ⚠️ Potential Challenges & Risks
- **Data Volume:** Large wallet histories might cause performance bottlenecks; consider lazy loading or summarization.
- **Risk Rule Accuracy:** False positives in alerts could annoy users; design rules carefully and allow tuning.
- **TUI Complexity:** Balancing rich data presentation with TUI constraints can be tricky; iterative UX testing needed.
- **Security:** Ensure no sensitive data exposure, especially in logs or alert messages.
- **Async Coordination:** Synchronizing wallet data fetching, analytics computations, and UI rendering without blocking.
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## 🔗 Resources & References
- [`tui-rs` crate documentation](https://docs.rs/tui) — for TUI components and rendering patterns.
- Solana RPC docs: https://docs.solana.com/developing/clients/jsonrpc-api — for transaction and balance queries.
- Rust async programming guide: https://rust-lang.github.io/async-book/
- Example crypto wallet analytics projects for inspiration:
- [Solana Explorer](https://explorer.solana.com/)
- [Ethereum Block Explorers](https://etherscan.io/)
- Project milestones and planning notes: #AI Development Plan Milestone #2
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Let's build a next-gen analytics dashboard that not only dazzles with data but empowers users to secure their crypto lives like pros! 💥
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### Checklist for Implementation
- [ ] Research and define wallet metrics and risk alerts
- [ ] Design TUI dashboard wireframes and architecture
- [ ] Implement wallet data collectors and analytics engine
- [ ] Build TUI dashboard components for visualization and alerts
- [ ] Integrate feature into CLI with commands and navigation
- [ ] Write comprehensive tests (unit, integration, UI)
- [ ] Conduct manual and user acceptance testing
- [ ] Update documentation and release notes
- [ ] Collect and incorporate user feedback for iteration
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**Assigned to:** _[Your Name or Team]_
**Estimated Size:** Large (L)
**Priority:** Should Have
**User Impact:** Medium
**Milestone:** AI Development Plan Milestone #2
