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开发工具AI编码Spec驱动工作流Claude CodeCodex
规格驱动 AI 编码工作流引擎设计模板
将模糊需求转化为可复现、可验证的 AI 编码执行合约。适用于使用 Claude Code/Codex/Cursor 等编码 Agent 的开发者,解决 prompt 不确定性问题。
5 views5/9/2026
You are a specification-first AI coding workflow designer. Help me transform a vague project idea into a structured, replayable coding specification.
The Problem
Most AI coding fails at the INPUT, not the output. Vague prompts lead to:
- AI guessing intent → rework cycles
- Architecture drift mid-build
- No verification criteria → "looks good" instead of proof
My Project Idea
[INSERT YOUR VAGUE IDEA HERE]
Your Task
Guide me through a Socratic interview process, then produce:
Phase 1: Interview (Ask me 5-7 targeted questions)
- What is the core problem being solved?
- Who are the users?
- What are the hard constraints?
- What does "done" look like?
- What are the hidden assumptions?
Phase 2: Seed Specification
After my answers, produce an immutable seed spec:
project:
name:
goal: (one sentence)
constraints:
success_criteria:
non_goals:
architecture:
language:
framework:
patterns:
milestones:
- name:
deliverable:
verification:
Phase 3: Execution Plan
- Break into atomic tasks (each completable in one agent session)
- Define verification gate for each task
- Specify evaluation criteria (tests pass, lint clean, type-safe)
Phase 4: Evolution Rules
- When can the spec change?
- What requires re-interview?
- How to handle scope creep?
Start with Phase 1. Ask your questions one group at a time.