Primitive Agents
1. Definition and Core Role
Primitive Agents are the atomic building blocks of REVOX’s decentralized AI agent ecosystem. Each Primitive Agent is designed to perform a single, narrowly scoped task with high reliability and auditability. By following the single responsibility principle, they provide predictable, secure, and composable functionality. This design ensures that agents remain lightweight, reusable, and independently auditable, while still forming the foundation for advanced, compound workflows.
In the REVOX ecosystem, Primitive Agents are comparable to the “Lego bricks” of decentralized intelligence. They are intentionally simple on their own, but when combined, they enable sophisticated workflows such as autonomous trading, compliance monitoring, data-driven governance, and prediction markets.
2. Architectural Principles
Minimalism and Modularity
Each agent focuses on one function only: signing transactions, fetching price data, analyzing charts, querying databases, or performing predictions.
Modularity allows agents to be upgraded, replaced, or reused independently without breaking higher-level workflows.
Security by Design
Local storage is encrypted, with support for hardware-based vaults for key management.
Agents operate within strict permission scopes, preventing unauthorized access to sensitive resources.
Role-based execution ensures that an agent designed for analytics cannot sign or broadcast transactions unless explicitly delegated.
Performance and Reliability
Primitive Agents follow strict performance benchmarks (latency <200ms for queries, >99.9% uptime for critical agents).
Built-in retry, fallback, and failover logic ensure reliability in real-world deployments.
Agents are load-tested to operate under high-concurrency scenarios, preparing them for millions of daily calls.
Transparency and Auditability
Every input, output, and execution path is logged in a verifiable format.
Logs can be persisted on-chain or in distributed storage, creating an immutable record for research, compliance, and forensic analysis.
3. Functional Categories of Primitive Agents
Wallet Agents
Handle address management, transaction signing, gas estimation, and secure broadcasting.
Provide APIs for both hot-wallet execution and cold-storage signing.
Equipped with customizable policies such as daily spending limits, multi-signature approval, or compliance filters.
Ticker Agents
Fetch real-time price feeds from decentralized exchanges and oracle networks.
Provide normalized, cached, and timestamped data streams to minimize latency.
Support anomaly detection, flagging price discrepancies across liquidity pools.
Chart & Analytics Agents
Aggregate and visualize historical market data.
Provide technical indicators (RSI, MACD, Bollinger Bands) directly callable by other agents.
Support predictive overlays, enabling trend-based decision-making.
Database Agents
Manage structured and unstructured storage for agents.
Enable efficient context retrieval (e.g., user history, KYC records, workflow states).
Designed for scalable querying across both on-chain and off-chain datasets.
Prediction Agents (New)
Lightweight ML-based forecasters that handle token price prediction, volatility estimation, or anomaly detection.
Integrated with proof-based validation (zkML) to provide verifiable inference.
Enable risk-sensitive applications like automated trading or fraud detection.
4. Security and Trust Framework
Isolated Execution Environment: Each agent runs in a sandbox, minimizing the blast radius of potential vulnerabilities.
Permissioned Capabilities: Developers declare agent capabilities explicitly, and permissions must be granted before deployment.
Cryptographic Guarantees: Integration with zkML ensures that outputs can be cryptographically verified.
Community Governance: Agents can be registered, rated, and reviewed in a decentralized registry, creating a reputation-based trust layer.
5. Application Scenarios
DeFi Automation: A combination of Wallet Agent + Ticker Agent + Prediction Agent enables a self-rebalancing portfolio strategy.
Compliance Monitoring: Database Agent + Analytics Agent can track suspicious transactions and feed alerts into governance workflows.
Data-driven Governance: Primitive Agents can monitor DAO proposals, analyze participation trends, and surface insights to stakeholders.
NFT and Gaming: Agents can fetch NFT metadata, validate ownership, and automate asset transfers during gameplay.
6. Interoperability with Other Building Blocks
Plugins: Primitive Agents call Plugins to access external APIs (e.g., off-chain market data, compliance services).
Context Knowledge: Primitive Agents query static or curated domain knowledge to enrich their decisions with historical or off-chain context.
Compound Agents: Multiple Primitive Agents are orchestrated into workflows, enabling multi-step autonomous behaviors.
DPrompt Oracle: Outputs from Primitive Agents can be verified on-chain, ensuring their correctness in mission-critical contracts.
7. Why Primitive Agents Are Foundational
By design, Primitive Agents ensure that REVOX remains secure, composable, and scalable. They embody three unique advantages:
Auditability: Unlike centralized AI APIs, Primitive Agents expose verifiable execution logs.
Flexibility: Any agent can be recombined to build new services, accelerating innovation.
Resilience: Modular design means failures in one agent do not compromise the entire system.
Ultimately, Primitive Agents are not just technical components—they are the bedrock of the decentralized AI agent economy. Their simplicity and reliability make them the perfect foundation for a scalable, transparent, and trust-minimized infrastructure.
Last updated