mcp-shrimp-task-manager/dist/tools/task/planTask.js

Shrimp Task Manager is a task tool built for AI Agents, emphasizing chain-of-thought, reflection, and style consistency. It converts natural language into structured dev tasks with dependency tracking and iterative refinement, enabling agent-like develope

import { z } from "zod";
import path from "path";
import { fileURLToPath } from "url";
import { getAllTasks } from "../../models/taskModel.js";
import { TaskStatus } from "../../types/index.js";
import { getPlanTaskPrompt } from "../../prompts/index.js";
import { getMemoryDir } from "../../utils/paths.js";
// 開始規劃工具
export const planTaskSchema = z.object({
    description: z
        .string()
        .min(10, {
        message: "任務描述不能少於10個字符，請提供更詳細的描述以確保任務目標明確",
    })
        .describe("完整詳細的任務問題描述，應包含任務目標、背景及預期成果"),
    requirements: z
        .string()
        .optional()
        .describe("任務的特定技術要求、業務約束條件或品質標準（選填）"),
    existingTasksReference: z
        .boolean()
        .optional()
        .default(false)
        .describe("是否參考現有任務作為規劃基礎，用於任務調整和延續性規劃"),
});
export async function planTask({ description, requirements, existingTasksReference = false, }) {
    // 獲取基礎目錄路徑
    const __filename = fileURLToPath(import.meta.url);
    const __dirname = path.dirname(__filename);
    const PROJECT_ROOT = path.resolve(__dirname, "../../..");
    const MEMORY_DIR = await getMemoryDir();
    // 準備所需參數
    let completedTasks = [];
    let pendingTasks = [];
    // 當 existingTasksReference 為 true 時，從數據庫中載入所有任務作為參考
    if (existingTasksReference) {
        try {
            const allTasks = await getAllTasks();
            // 將任務分為已完成和未完成兩類
            completedTasks = allTasks.filter((task) => task.status === TaskStatus.COMPLETED);
            pendingTasks = allTasks.filter((task) => task.status !== TaskStatus.COMPLETED);
        }
        catch (error) { }
    }
    // 使用prompt生成器獲取最終prompt
    const prompt = await getPlanTaskPrompt({
        description,
        requirements,
        existingTasksReference,
        completedTasks,
        pendingTasks,
        memoryDir: MEMORY_DIR,
    });
    return {
        content: [
            {
                type: "text",
                text: prompt,
            },
        ],
    };
}
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