بنقرة واحدة
deep-interview
Socratic requirements clarification before any code is written
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Socratic requirements clarification before any code is written
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Full autonomous execution from idea to working code
Production-grade Docker configurations (Dockerfile, Compose, best practices)
Persistence mode — doesn't stop until the task is verified complete
Multi-agent coordinated execution
Autonomous QA cycling until all tests pass
Maximum parallel throughput — execute independent tasks simultaneously
| name | deep-interview |
| description | Socratic requirements clarification before any code is written |
| argument-hint | <vague idea or concept> |
| level | 4 |
<Use_When>
<Do_Not_Use_When>
<Interview_Protocol>
CRITICAL: Ask ONE question at a time. Wait for response before asking the next.
Do NOT dump all questions at once. Each question must be followed by a response prompt:
❯ [question]
> _
After the user responds, analyze their answer, then ask the next relevant question.
Ask ONE question:
"What is the primary goal of this [feature]? What problem does it solve?"
Wait for response.
Ask ONE question:
"Who will be using this? (developers, end users, admins, etc.)"
Wait for response.
Based on answers, ask ONE focused question about scope:
"What features are essential vs nice-to-have?"
Wait for response.
Based on answers, ask ONE question about tech:
"Do you have existing preferences for [language/framework/database]?"
Wait for response.
Ask ONE question about constraints:
"Any specific requirements around [security/scale/compliance]?"
Wait for response.
Ask ONE question about edge cases:
"What should happen if [edge case]?"
Wait for response.
After all questions, if you have enough information (>80% clarity):
Generate SPEC.md with:
Then inform the user:
❯ SPEC.md generated. Here's what I understood:
## Summary
[2-3 sentences max]
## Core Features
1. [Feature 1] - Must have
2. [Feature 2] - Must have
3. [Feature 3] - Nice to have
## Next Step
Should I create a detailed PLAN.md with:
- File structure
- Tech stack recommendations
- Implementation steps
- Effort estimate
Type "yes" to proceed with the plan, or tell me if I missed something.
If unclear (>20% ambiguity):
"I still have some open questions about [specific topics]. Let me ask..."
Ask remaining questions one by one.
After generating SPEC.md:
</Interview_Protocol>
After the interview, produce a SPEC.md with: - Problem statement - Target users - Core features (with priorities) - User workflows - Edge cases to handle - Constraints - Open questions (if any)This spec becomes the input for planning or autopilot.
<Ambiguity_Gate> If after questioning, ambiguity is still > 20%, flag specific unknowns before proceeding.
If ambiguity is acceptable (< 20%), proceed to spec generation. </Ambiguity_Gate>
User: "deep-interview I want to build something for tracking my tasks" Assistant: "What is the primary goal of this task tracker? What problem does it solve?"User: "I want to track daily tasks and see my productivity over time" Assistant: "Who will be using this tracker?" ... Why good: One question at a time, builds understanding progressively
User: "deep-interview build a REST API for POST /users with body {name, email}" Why bad: Requirements are already specific - no interview needed<Anti_Pattern>
❌ DO NOT output all questions at once:
Round 1: Scope
1. What is the primary goal?
2. Who are the end users?
3. What does success look like?
Round 2: Technical
1. Tech stack?
2. Database preferences?
...
This overwhelms the user and prevents clarification.
✅ Ask one, wait, ask next:
❯ What is the primary goal of this feature?
> user responds
❯ Who will be using it?
> user responds
❯ Any tech stack preferences?
> user responds
...
</Anti_Pattern>