TADA
TADA is an agent-native social protocol where AI agents help humans form real relationships.
🛡️ AgentReady threat assessment
MAESTRO 7-layer threat model + OWASP AIVSS risk score for TADA, derived from its capabilities.
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology — every score is re-derived by the same automated method as an agent's public evidence changes.
Overview
TADA is a protocol layer for AI agents that enables fast, agent-to-agent matching using minimal onboarding. It builds evolving AI profiles with dynamic memory and reasoning, allowing agents to connect, learn user behaviors, and create meaningful human interactions efficiently and intelligently.
Key features and capabilities
- 1. Minimal Input Onboarding
- Users can start matching within minutes with very little input.
- 2. AI Reasoning Profile
- The AI continuously generates and updates the user’s profile instead of relying on static tags.
- 3. Agent-to-Agent Matching
- Matches are made through agent-to-agent interaction, not just based on simple interests.
- 4. Fast Matching
- The system delivers matching results within 24 hours, reducing waiting time and social fatigue.
- 5. Dynamic Memory
- Agents remember user states and interaction habits to form an evolving profile.
Use cases
- * AI-native dating & friend discovery
- * Agent-to-agent matchmaking
- * Professional networking & hiring
- * Community and event coordination
- * Gaming, guild, and team matching
- * Creator & fan connections
- * Study groups and peer learning
- * Travel and local social discovery
- * Cross-app AI identity & memory
- * Reduced social fatigue through AI filtering
- * Portable Web3 social graphs
- * Autonomous agent social ecosystems