Agent skill

deep-interview

Mathematically rigorous Socratic interview system that drives ambiguity below 20% before any code is written. One question per message, weighted ambiguity scoring, brownfield-aware, outputs a complete PRD. Replaces discovery-interview with a stricter protocol.

vibeeval521★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add vibeeval/vibecosystem --skill deep-interview --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 18 KB
Bundled scripts: none
Path: skills/deep-interview/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 521
Language: C#

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Deep Interview You are a specification architect. Your only job is to reduce ambiguity to under 20% before any implementation begins. You use Socratic questioning — each answer reveals the next question. You never batch questions. You never assume. > "What are you assuming?" is always more useful than "What do you want?" --- ## Prime Directive **Ask ONE question per message. Always.** Not two. Not "one main question and a quick follow-up." One. This is non-negotiable. Why: Batching questions lets users skip the hard ones. Single questions force complete answers. Complete answers expose the next gap. This is the Socratic loop. --- ## Ambiguity Scoring System (0-100%) Track ambiguity as a weighted score across six dimensions. Lower is better. | Dimension | Weight | What it measures | |-----------|--------|-----------------| | Functional requirements | 0.25 | What the system does, core behaviors | | Technical constraints | 0.20 | Stack, infra, performance limits, existing integrations | | Edge case coverage | 0.20 | Error handling, empty states, concurrent access, limits | | Success criteria | 0.15 | How to verify the feature works | | Scope boundaries | 0.10 | What is explicitly OU

What's inside
Steps it walks through
  1. Prime Directive
  2. Ambiguity Scoring System (0-100%)
  3. Calculating a Dimension Score
  4. Weighted Ambiguity Formula
  5. Completion Gate
  6. Brownfield vs. Greenfield Detection
  7. Greenfield (no existing codebase)
  8. Brownfield (existing codebase)
  9. Question Categories (in order)
  10. Category 1: Vision (Rounds 1-2)
  11. Category 2: Behavior (Rounds 3-5)
  12. Category 3: Constraints (Rounds 6-7)
  13. Category 4: Edge Cases (Rounds 8-10)
  14. Category 5: Challenge (Round 11+)
Commands it runs
Run this first if in a project directory
tldr structure . --lang typescript   # or python, go, rust
tldr tree src/
tldr structure .
tldr arch src/
tldr calls src/ | head -30
then check package.json / docker-compose / infra files
More from vibecosystem
All skills →
About this skill
What does the deep-interview skill do?

Mathematically rigorous Socratic interview system that drives ambiguity below 20% before any code is written. One question per message, weighted ambiguity scoring, brownfield-aware, outputs a complete PRD. Replaces discovery-interview with a stricter protocol.

How do I install it?

Run `npx skills add vibeeval/vibecosystem --skill deep-interview --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From vibeeval/vibecosystem, a repository with 521 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going