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interview
Interview me about a plan to flesh out requirements before implementation. Asks non-obvious questions one at a time until all ambiguities are resolved.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Interview me about a plan to flesh out requirements before implementation. Asks non-obvious questions one at a time until all ambiguities are resolved.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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| name | interview |
| description | Interview me about a plan to flesh out requirements before implementation. Asks non-obvious questions one at a time until all ambiguities are resolved. |
| argument-hint | <plan-file> |
| model | claude-opus-4-5-20251101 |
Systematically interview the user about their plan/PRD to surface and resolve ambiguities BEFORE implementation begins. This prevents wasted iterations in Ralph loops by ensuring the spec is tight.
Credit: @trq212's interview method, documented by @callam53.
When invoked with /interview <plan-file>:
Systematically cover these areas:
Always use AskUserQuestion with a single, focused question. Never batch questions.
Bad: "What technology should we use, and what about error handling, and also what's the timeline?"
Good: "For the transcription service - Recall.ai vs Google Speech API vs Deepgram. Which direction are you leaning and why?"
When an answer reveals new ambiguity, follow up immediately:
User: "We'll use Recall.ai for transcription"
Follow-up: "Recall.ai has both real-time webhooks and polling. For your latency needs, which pattern makes more sense?"
Skip questions with obvious answers. Focus on:
Stop interviewing when:
When interview is complete:
Summarize findings in structured format:
## Interview Summary: [Plan Name]
### Decisions Made
- [Decision 1]: [Choice and rationale]
- [Decision 2]: [Choice and rationale]
### Clarifications
- [Ambiguity]: [Resolution]
### Edge Cases Addressed
- [Case]: [How to handle]
### Remaining Open Questions
- [Question]: [Why it's ok to defer]
### Constraints Confirmed
- [Constraint]: [Details]
Ask where to write the summary:
plan-interview-notes.md)Update the plan file if user wants inline updates
/interview docs/atlas-on-calls/PROMPT.md
[Reads file]
"I've read the Atlas on Calls plan. I have questions about several areas. Let's start with the most critical:
For trigger detection - you mention 'atlas' as the wake word. What should happen if someone says 'Atlas is our AI assistant' (mention but not a question) vs 'Atlas, what's our revenue?' (actual query). How sophisticated does this detection need to be for v1?"
[User answers]
"Got it - simple pattern matching for v1, upgrade later. Follow-up: For the chat trigger '@atlas', should it require the @ symbol, or also match 'atlas,' or 'hey atlas'?"
[User answers]
"Clear. Moving to a different area - Recall.ai pricing. Have you confirmed their pricing model works for your expected call volume? This could affect architecture if there are per-minute costs."
[... continues until done ...]
"I think we've covered the critical ambiguities. Here's a summary of what we resolved:
[Summary]
Where should I save these notes?"
This skill fits in the pre-Ralph workflow:
1. Write rough prd.md / plan idea
2. /brainstorming (optional - if approach unclear)
3. /interview prd.md <-- THIS SKILL
4. Update plan with interview findings
5. /ralph-loop or ralph-import
The interview ensures your Ralph prompt is tight enough that Claude doesn't waste iterations on ambiguous requirements.
During interview:
At summary: