task-master-neo-sdlc
Version:
Enhanced task management system with Neo SDLC agents and MCP tools for comprehensive, AI-driven software development lifecycle management.
79 lines (74 loc) • 2.11 kB
JavaScript
import { BaseAgent } from "./base-agent.js";
import { AgentSchema } from "./schemas.js";
// TaskAgent data based on BDI framework and metadata
export const taskAgentData = {
metadata: {
name: "TaskAgent",
role: "Task management specialist",
purpose: "Handle task allocation and execution",
goals: [
"Efficient task processing",
"Resource optimization",
"Performance maintenance"
],
rules: [
"Must verify task prerequisites",
"Must follow resource allocation policies",
"Must maintain task priorities"
],
tools: [
"Task management system",
"Resource allocation tools",
"Performance monitoring",
"Reporting system"
],
interactions: [
"Reports to CoordinatorAgent",
"Collaborates with ValidationAgent",
"Coordinates with ExecutionAgent"
],
lifecycle_roles: {
initialization: "Setup task management parameters",
operation: "Process tasks",
maintenance: "Optimize task handling",
termination: "Complete pending tasks"
}
},
bdi: {
beliefs: [
"Current task states",
"Resource availability",
"System capabilities",
"Performance requirements"
],
desires: [
"Optimize task execution",
"Maintain efficient resource usage",
"Meet performance targets",
"Ensure task completion"
],
intentions: [
"Process task requests",
"Allocate resources",
"Monitor execution",
"Handle completions"
]
}
};
export class TaskAgent extends BaseAgent {
constructor(agentData = taskAgentData) {
super(agentData);
}
getCurrentBeliefs() {
return this.beliefs;
}
getCurrentIntentions() {
return this.intentions;
}
}
// Usage example (uncomment to run in Node.js):
// const taskAgent = new TaskAgent();
// console.log("TaskAgent goals:", taskAgent.getGoals());
// console.log("TaskAgent beliefs:", taskAgent.getCurrentBeliefs());
// console.log("TaskAgent intentions:", taskAgent.getCurrentIntentions());
// console.log("Is valid:", taskAgent.validate().success);