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Agent skill

Deep Interview

by zereight in zereight/gitlab-mcp

Socratic deep interview with mathematical ambiguity gating. An agent skill from zereight/gitlab-mcp.

MITAuto-check passedAgent Workflows

Install Deep Interview

skills CLI
$ npx skills add zereight/gitlab-mcp --skill deep-interview -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zereight/gitlab-mcp deep-interview --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zereight/gitlab-mcp.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/deep-interview .claude/skills/deep-interview && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deep-interview
GitHub stars
2k
Used in
1 other repo
Token cost
~725 tokens
SKILL.md length
326 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
MIT

At a glance

Socratic deep interview with mathematical ambiguity gating. An agent skill from zereight/gitlab-mcp.

  • Works in 5 steps: Initialize → Interview Loop → Challenge Agents → …
  • Says: deep interview
  • SKILL.md covers Pipeline, When to Use, When NOT to Use and Phases, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Deep Interview is an agent skill from zereight/gitlab-mcp. Socratic deep interview with mathematical ambiguity gating. Activate when user says: deep interview, interview me, ask me everything, don't assume, make sure you understand, ouroboros, socratic, I have a vague idea, not sure exactly what I want.

Its SKILL.md is about 730 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Agent Workflows, covering Tutoring and explanations and Requirements gathering. The repository describes itself as: First gitlab mcp for you, building together. The licence is MIT.

When your agent uses it

  • Says: deep interview
  • Ask me everything
  • Make sure you understand
  • I have a vague idea

Example prompts

  • “/deep-interview”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Initialize
  2. Interview Loop
  3. Challenge Agents
  4. Crystallize Spec
  5. Execution Bridge

What it can do on your machine

Read from SKILL.md and the folder at commit 0109168. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deep Interview loads about 725 tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 326 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~725

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from zereight/gitlab-mcp at commit 0109168, republished under its MIT licence (© zereight). 326 words, ~725 tokens.

Download SKILL.mdSave it as .claude/skills/deep-interview/SKILL.md (or your agent's skills folder).
name
deep-interview
description
Socratic deep interview with mathematical ambiguity gating. Activate when user says: deep interview, interview me, ask me everything, don't assume, make sure you understand, ouroboros, socratic, I have a vague idea, not sure exactly what I want.
argument-hint
[--quick|--standard|--deep] <idea or vague description>

Deep Interview

Ouroboros-inspired Socratic questioning with mathematical ambiguity scoring. Replaces vague ideas with crystal-clear specifications by asking targeted questions that expose hidden assumptions.

Pipeline

deep-interview → ralplan (consensus refinement) → omg-autopilot (execution)

When to Use

  • User has a vague idea and wants thorough requirements gathering
  • Task is complex enough that jumping to code would waste cycles
  • User wants mathematically-validated clarity before execution

When NOT to Use

  • Detailed specific request with file paths → execute directly
  • Quick fix → delegate to @executor or /ralph
  • User says "just do it" → respect their intent

Phases

Phase 1: Initialize
  1. Parse the user's idea
  2. Detect brownfield vs greenfield (use @explore to check codebase)
  3. For brownfield: map relevant codebase areas
  4. Initialize ambiguity score at 100%
Phase 2: Interview Loop

Repeat until ambiguity <= 20% or user exits early:

  1. Generate question targeting the WEAKEST clarity dimension
  2. Ask ONE question at a time with current ambiguity context
  3. Score ambiguity across dimensions:
    • Goal Clarity (40% weight for greenfield, 35% brownfield)
    • Constraint Clarity (30% / 25%)
    • Success Criteria (30% / 25%)
    • Context Clarity (N/A / 15% for brownfield)
  4. Report progress with dimension scores and gaps
  5. Track ontology (key entities, stability ratio)
Phase 3: Challenge Agents
  • Round 4+: Contrarian - challenge core assumptions
  • Round 6+: Simplifier - probe for complexity removal
  • Round 8+: Ontologist - find the essence (if ambiguity > 30%)
Phase 4: Crystallize Spec

When ambiguity <= threshold, generate spec to .omc/specs/deep-interview-{slug}.md:

  • Goal, Constraints, Non-Goals, Acceptance Criteria
  • Assumptions Exposed & Resolved
  • Ontology (Key Entities) with convergence tracking
  • Interview Transcript
Phase 5: Execution Bridge

Present options:

  1. Ralplan → OMG Autopilot (Recommended): consensus-refine then execute
  2. Execute with omg-autopilot (skip ralplan)
  3. Execute with ralph: persistence loop
  4. Execute with team: parallel agents
  5. Refine further: continue interviewing

Rules

  • Ask ONE question at a time
  • Target the WEAKEST clarity dimension each round
  • Gather codebase facts via @explore BEFORE asking user
  • Score ambiguity after every answer
  • Do not proceed until ambiguity <= threshold (default 20%)
  • Hard cap at 20 rounds, soft warning at 10

© zereight, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/deep-interview of zereight/gitlab-mcp.

Open the folder on GitHubat commit 0109168

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in zereight/gitlab-mcp, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Deep Interview next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Deep Interview compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deep Interview this skillzereight/gitlab-mcp2k1 repos~725Automated safety check: PassMIT
Ralphaiskillstore/marketplace4301 repos~4.2kAutomated safety check: NotesNone
Hoyeon Discussteam-attention/hoyeon173—~458Automated safety check: PassMIT
Deep Divebyungjunjang/jangpm-meta-skills121—~2.7kAutomated safety check: PassNone
Deep Divebyungjunjang/jangpm-meta-skills121—~2.5kAutomated safety check: PassNone
Grill Mesoftspark/ai-toolkit179—~732Automated safety check: NotesApache-2.0

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Categories

Questions about Deep Interview

What does Deep Interview do?

Socratic deep interview with mathematical ambiguity gating. An agent skill from zereight/gitlab-mcp. Deep Interview is an agent skill from zereight/gitlab-mcp. Socratic deep interview with mathematical ambiguity gating.

When should I use Deep Interview?

Deep Interview fits situations like: says: deep interview; ask me everything; make sure you understand; I have a vague idea.

How do I install Deep Interview in Claude Code?

Run `npx skills add zereight/gitlab-mcp --skill deep-interview -a claude-code`. Or copy the skill folder (.github/skills/deep-interview in zereight/gitlab-mcp) into .claude/skills/deep-interview in your project. Claude Code loads it when a task matches its description.

How do I install Deep Interview in Codex?

Run `npx skills add zereight/gitlab-mcp --skill deep-interview -a codex`. Or copy the skill folder (.github/skills/deep-interview in zereight/gitlab-mcp) into .agents/skills/deep-interview in your project. Codex loads it when a task matches its description.

Can I use Deep Interview in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zereight/gitlab-mcp --skill deep-interview -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-interview, .gemini/skills/deep-interview, .github/skills/deep-interview and .opencode/skills/deep-interview in your project.

What does Deep Interview need to run?

SKILL.md names no scripts, command-line tools or credentials: Deep Interview is instructions for the agent only.

Does Deep Interview access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Deep Interview safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deep Interview use?

Deep Interview is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deep Interview use?

About 725 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deep Interview?

Skills that share tags, products or a category with Deep Interview: Ralph (aiskillstore/marketplace, 430 stars), Hoyeon Discuss (team-attention/hoyeon, 173 stars), Deep Dive (byungjunjang/jangpm-meta-skills, 121 stars) and Deep Dive (byungjunjang/jangpm-meta-skills, 121 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Interview?

zereight (a GitHub user) maintains it in zereight/gitlab-mcp, which has 2,027 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 6, 2026.

Source: zereight/gitlab-mcp on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.