intentkit

IntentKit initializes and manages multiple AI agents using LangGraph as the underlying execution framework, storing agent configurations in a persistent database and routing user requests through a centralized Agent Engine that coordinates skill execution, memory management, and state transitions. Each agent maintains its own configuration, prompt templates, and skill bindings, enabling independent behavior while sharing the same infrastructure layer.

IntentKit provides an IntentKitSkill base class that allows developers to define new agent capabilities through a modular skill framework. Skills are registered with schemas and configurations that control their behavior, stored in a skill store for persistence, and dynamically loaded into agents at runtime. The system supports categorized skills including blockchain, social media, and financial data operations, with each skill maintaining its own state and configuration.

IntentKit includes a plugin system architecture (currently in development) that will enable developers to extend agent capabilities through plugins beyond the skill framework. The plugin system is designed to support dynamic loading of capability modules without framework recompilation. While the full plugin system is not yet complete, the architecture is in place to support third-party plugin development alongside the core skill system.

IntentKit includes pre-built blockchain skills that enable agents to interact with Ethereum Virtual Machine (EVM) compatible chains. These skills are implemented as specialized IntentKitSkill subclasses that handle wallet operations, smart contract interactions, transaction execution, and on-chain data queries. The blockchain skill layer abstracts away low-level Web3 complexity while maintaining full control over transaction parameters and execution.

IntentKit provides native integration with Telegram and Twitter as entrypoints, allowing agents to receive messages from these platforms, process them through the agent engine, and respond directly. The system maintains conversation context across platform interactions, routes incoming messages to appropriate agents based on configuration, and handles platform-specific formatting and authentication. Each platform integration is implemented as a separate entrypoint that feeds into the core agent execution layer.

IntentKit implements a credit management system that tracks agent usage and enforces quotas across different account types (user, agent, platform). The system supports three credit types (FREE with daily refills, PERMANENT from top-ups, REWARD earned through activities) and tracks both income events (recharge, reward, refill) and expense events (message, skill call). Credits are deducted per agent action, enabling fine-grained usage tracking and cost allocation across multiple agents and users.

IntentKit enables agents to run autonomously on schedules without manual intervention. The system stores scheduling configurations in the database, executes agents at specified intervals through a scheduler component, and maintains execution logs for monitoring. Autonomous execution integrates with the core agent engine, allowing scheduled agents to access all skills and entrypoints available to manually-triggered agents, with full state and memory preservation across execution cycles.

IntentKit maintains persistent memory storage for agent conversations and state across sessions. The system stores conversation history, agent context, and skill-specific data in a dedicated memory layer, enabling agents to recall previous interactions and maintain coherent behavior across multiple invocations. Memory is indexed by agent and conversation ID, allowing agents to retrieve relevant context when processing new requests through any entrypoint.

IntentKit exposes a Web API that allows external systems to invoke agents, manage agent configurations, and query execution results. The API provides RESTful endpoints for agent creation, skill configuration, message submission, and result retrieval. The Web API integrates with the core agent engine and credit system, enforcing quotas and logging all API interactions for auditing. API authentication is handled through API keys or user credentials, with role-based access control for agent management.

IntentKit includes pre-built skills for accessing financial and market data, enabling agents to query price feeds, market conditions, and financial metrics. These skills are implemented as specialized IntentKitSkill subclasses that integrate with external financial data providers and cache results to minimize API calls. Agents can use these skills to make informed decisions in trading, DeFi, or investment workflows, with data freshness and accuracy controlled through skill configuration.

IntentKit stores agent configurations in a persistent database, enabling agents to be created, modified, and retrieved without code changes. Agent configurations include prompts, skill bindings, model selection, and execution parameters. The system maintains agent schemas and allows configuration export/import through scripts, though full versioning and rollback capabilities are not yet implemented. Configuration changes are applied immediately to running agents without requiring restart.