interview-framework

仓库创建 2026年1月12日最近提交 4 天前SkillHot 收录 21 天前

▸ 精选理由

结构化访谈算法，能在规格各阶段高效收集澄清信息。

这个 Skill 做什么

用于交互式需求访谈，按相位引导问题并生成选项化决策路径。

用来做交互式需求访谈，按“理解问题—提出方案—确认并存档”三阶段引导对话，边问边给用户 2–4 个有针对性的选项来缩小范围。适合在正式写 spec 或分配任务前，通过对话厘清需求和优先级。特点是结构化且可选项限制在 2–4 个，方便快速达成共识并把结论记进记忆库。

▸ 展开 SKILL.md 英文原文

This skill should be used when running an interactive interview before a spec phase, gathering requirements through dialogue, asking the user clarifying questions before delegating to a subagent, or when any Ralph phase command (research, requirements, design, tasks) needs adaptive brainstorming dialogue. Covers the 3-phase algorithm (Understand, Propose Approaches, Confirm and Store).

开发编程访谈引导需求采集交互式通用

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SKILL.MD 节选查看完整文件 ↗

# Interview Framework

Adaptive brainstorming dialogue algorithm for all spec phases. Each phase command provides its own exploration territory (phase-specific areas to probe).

## Option Limit Rule

Each question must have 2-4 options (max 4). Keep the most relevant options, combine similar ones.

## Recommendation Format

Every question asked via `AskUserQuestion` in Phase 1 leads with the recommended option (except when options are symmetric, in which case `[Recommended]` may be omitted):

```yaml
AskUserQuestion:
  question: "[Context-aware question referencing prior answers]. [One sentence rationale for the recommendation.]"
  options:
    - "[Recommended] [Option text -- the AI's sugge

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