CCTools 159 Milestone 1: Learn-to-Earn & Discovery Platform

Milestone 1: Learn-to-Earn & Discovery Platform

| Detail | Description | |--------|-------------| | Estimated Delivery | Month 1 from grant approval | | Focus | Educational platform, featured apps, advanced data integrations, governance analytics | | Funding | 200,000 CC |

This milestone is prioritized first to establish CCTools as an educational and discovery hub for Canton Network. The platform should be the go-to destination for any user who wants to explore, understand, and learn about Canton. Learn-to-earn content drives genuine engagement with the ecosystem and creates a monetizable product (project-sponsored quests).

Deliverables:

• Learn-to-Earn System: Structured learning paths covering Canton fundamentals, DeFi concepts, ecosystem exploration, and advanced topics. Each path contains multiple quests with educational modules, quizzes, and knowledge checks. Users earn XP and exclusive badges upon completion. Projects can sponsor quests to educate users about their product while driving real understanding.

- Learning paths: Canton Fundamentals, DeFi on Canton, Ecosystem Explorer, Advanced Topics - Quest system with modules, questions, and completion verification - XP rewards and exclusive Learn badges (First Lesson, Canton Scholar, DeFi Graduate, Ecosystem Expert, Canton Master) - Project-sponsored quest framework (monetizable: projects pay to create educational content about their product)

• Featured Apps Pages: Dedicated pages for each Canton Featured App with on-chain data linked to their party addresses. Real-time rewards tracking, transaction activity, and performance metrics pulled directly from the Global Synchronizer. Curated project profiles with team information, FAQ, and comparison tools. Mapping of on-chain identities to ecosystem projects for seamless discovery.
• Enhanced Validators Directory: Improved validator pages linking on-chain party addresses to ecosystem project profiles. Validator performance metrics, reward history, uptime tracking, and commission data. Super Validator governance participation and voting patterns. Visual mapping of which projects operate which validators.
• Advanced Data Integrations: Partnership with data providers (CantonScan, CC View) for structured on-chain data. Integration of third-party APIs to enrich ecosystem directory with real-time metrics, transaction volumes, and activity data. On-chain identity resolution connecting party addresses to known projects and validators.
• Ecosystem Directory Redesign: Rebuilt ecosystem experience with improved project pages, richer filtering, category navigation, and enhanced project analytics. Better discovery flow for new users to find and compare projects across categories. Improved submission and edit workflows for community contributions.
• Project Scoring Methodology (public and transparent): The current scoring system uses algorithmic and AI evaluation based on project metadata: description, team, funding, documentation, social presence, and network roles. It scores five dimensions (transparency, activity, community, documentation, maturity) and combines the AI result (60%) with a deterministic completeness bonus (40%) based on filled fields. This produces a 0-100 score per project. The upgraded scoring will integrate real on-chain signals from Canton Network: active validators, featured app status, and accumulated rewards will directly influence the score. Projects running validators or featured apps on Canton will receive higher activity and maturity scores based on verifiable on-chain data, not self-reported information. Users will be able to click on any project's score to open a detailed breakdown modal explaining exactly how the score was calculated, which dimensions contributed, and what on-chain data was considered. A public methodology page will document the scoring criteria, data sources, and weighting so anyone can understand and verify the ratings. This addresses the need for editorial transparency and objective quality signals in the ecosystem directory.
• Governance Analytics: Enhanced proposal tracking with historical voting patterns, validator participation rates, voting trend analysis, and proposal outcome statistics. Visual dashboards for governance health metrics.

Acceptance Criteria:

• Learn-to-earn system live with at least 3 learning paths and 10+ quests
• Featured Apps pages live with on-chain data linked to party addresses
• Enhanced validators directory live with project-to-validator mapping
• Redesigned ecosystem directory live with improved discovery and filtering
• Project scoring methodology page live with public documentation of criteria, and score breakdown modal accessible on every project page
• At least 1 data provider integration active and serving enriched data
• Governance analytics dashboard live with historical data
• User engagement: measurable increase in daily active users