mcp-chain-of-thought/dist/prompts/generators/updateTaskContent.js

Chain of Thought is a 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 developer behavi

/**
 * updateTaskContent prompt generator
 * Responsible for combining templates and parameters into the final prompt
 */
import { loadPrompt, generatePrompt, loadPromptFromTemplate, } from "../loader.js";
/**
 * Get the complete updateTaskContent prompt
 * @param params prompt parameters
 * @returns generated prompt
 */
export function getUpdateTaskContentPrompt(params) {
    const { taskId, task, success, message, validationError, emptyUpdate, updatedTask, } = params;
    // Handle case where task doesn't exist
    if (!task) {
        const notFoundTemplate = loadPromptFromTemplate("updateTaskContent/notFound.md");
        return generatePrompt(notFoundTemplate, {
            taskId,
        });
    }
    // Handle validation error case
    if (validationError) {
        const validationTemplate = loadPromptFromTemplate("updateTaskContent/validation.md");
        return generatePrompt(validationTemplate, {
            error: validationError,
        });
    }
    // Handle empty update case
    if (emptyUpdate) {
        const emptyUpdateTemplate = loadPromptFromTemplate("updateTaskContent/emptyUpdate.md");
        return generatePrompt(emptyUpdateTemplate, {});
    }
    // Handle successful or failed update case
    const responseTitle = success ? "Success" : "Failure";
    let content = message || "";
    // Success update with updated task details
    if (success && updatedTask) {
        const successTemplate = loadPromptFromTemplate("updateTaskContent/success.md");
        // Compile related files information
        let filesContent = "";
        if (updatedTask.relatedFiles && updatedTask.relatedFiles.length > 0) {
            const fileDetailsTemplate = loadPromptFromTemplate("updateTaskContent/fileDetails.md");
            // Group files by type
            const filesByType = updatedTask.relatedFiles.reduce((acc, file) => {
                if (!acc[file.type]) {
                    acc[file.type] = [];
                }
                acc[file.type].push(file);
                return acc;
            }, {});
            // Generate content for each file type
            for (const [type, files] of Object.entries(filesByType)) {
                const filesList = files.map((file) => `\`${file.path}\``).join(", ");
                filesContent += generatePrompt(fileDetailsTemplate, {
                    fileType: type,
                    fileCount: files.length,
                    filesList,
                });
            }
        }
        // Process task notes
        const taskNotesPrefix = "- **Notes:** ";
        const taskNotes = updatedTask.notes
            ? `${taskNotesPrefix}${updatedTask.notes.length > 100
                ? `${updatedTask.notes.substring(0, 100)}...`
                : updatedTask.notes}\n`
            : "";
        // Generate detailed information for successful update
        content += generatePrompt(successTemplate, {
            taskName: updatedTask.name,
            taskDescription: updatedTask.description.length > 100
                ? `${updatedTask.description.substring(0, 100)}...`
                : updatedTask.description,
            taskNotes: taskNotes,
            taskStatus: updatedTask.status,
            taskUpdatedAt: new Date(updatedTask.updatedAt).toISOString(),
            filesContent,
        });
    }
    const indexTemplate = loadPromptFromTemplate("updateTaskContent/index.md");
    const prompt = generatePrompt(indexTemplate, {
        responseTitle,
        message: content,
    });
    // Load possible custom prompt
    return loadPrompt(prompt, "UPDATE_TASK_CONTENT");
}
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