17th-task-architect

Orchestrate GPT-5.2 xhigh and GLM-4.7 to produce a finalized TASK.md.

Updated Jan 23, 2026
One-click install
npx skills add https://github.com/SeventeenthEarth/glm-worker-mcp --skill 17th-task-architect
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 17th-task-architect
Source: https://github.com/SeventeenthEarth/glm-worker-mcp/tree/main/skills/17th-task-architect
Command: npx skills add https://github.com/SeventeenthEarth/glm-worker-mcp --skill 17th-task-architect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the end-to-end TASK specification design by coordinating GPT-5.2 xhigh with GLM-4.7 to elicit requirements, run parallel research, and resolve ambiguities through interviews, ultimately producing a finalized TASK.md.

Core Features & Use Cases

  • End-to-end TASK design orchestration: elicitation, parallel research, synthesis, interviews, and final TASK.md.
  • Generates a concrete TASK.md with specific file paths, decisions, and a clear execution checklist.
  • Ideal for planning complex features, roadmaps, and implementation plans with reproducible documentation.

Quick Start

Use the Task Architect workflow to design a new TASK specification by coordinating GPT-5.2 xhigh and GLM-4.7, eliciting requirements, running parallel research, synthesizing results, and interviewing the user to produce a finalized TASK.md.

Frequently Asked Questions about 17th-task-architect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate project planning and generate a TASK.md specification?

To automate project planning, this Skill orchestrates AI agents to elicit requirements, run parallel research, and synthesize results into a finalized TASK.md with specific file paths and execution checklists.

What is workflow automation for design specs using multiple AI agents?

Workflow automation for design specs coordinates GPT-5.2 xhigh and GLM-4.7 to resolve ambiguities through an interview loop, producing reproducible documentation for complex features and implementation plans.

How do I orchestrate AI agents to create reproducible implementation plans?

You orchestrate AI agents by initiating the Task Architect workflow, which coordinates GPT-5.2 xhigh and GLM-4.7 to conduct interviews and finalize a concrete TASK.md execution checklist.

Can I use GPT-5.2 and GLM-4.7 together for complex feature roadmap design?

Yes, you can use GPT-5.2 xhigh and GLM-4.7 together to plan complex feature roadmaps, coordinating the models to elicit requirements and synthesize parallel research into a final TASK.md.

What is the best way to resolve requirement ambiguities during TASK.md generation?

The best way to resolve requirement ambiguities during TASK.md generation is using the integrated interview loop, which questions the user to clarify decisions before finalizing the design spec.