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Agent skill

Deep Dive

by zereight in zereight/gitlab-mcp

2-stage pipeline: trace (causal investigation) then deep-interview (requirements).

MITAuto-check passed

Install Deep Dive

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

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

GitHub CLI
$ gh skill install zereight/gitlab-mcp deep-dive --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-dive .claude/skills/deep-dive && 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-dive
GitHub stars
2k
Used in
1 other repo
Token cost
~536 tokens
SKILL.md length
233 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
MIT

At a glance

2-stage pipeline: trace (causal investigation) then deep-interview (requirements).

  • Works in 5 steps: Initialize → Lane Confirmation → Trace Execution → …
  • Says: deep dive
  • 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 Dive is an agent skill from zereight/gitlab-mcp. 2-stage pipeline: trace (causal investigation) then deep-interview (requirements). Activate when user says: deep dive, deep-dive, investigate deeply, trace and interview.

Its SKILL.md is about 540 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: First gitlab mcp for you, building together. The licence is MIT.

When your agent uses it

  • Says: deep dive
  • Investigate deeply
  • Trace and interview

Example prompts

  • “/deep-dive”

Workflow steps

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

  1. Initialize
  2. Lane Confirmation
  3. Trace Execution
  4. Interview with Trace Injection
  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 Dive loads about 536 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 233 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~536

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). 233 words, ~536 tokens.

Download SKILL.mdSave it as .claude/skills/deep-dive/SKILL.md (or your agent's skills folder).
name
deep-dive
description
2-stage pipeline: trace (causal investigation) then deep-interview (requirements). Activate when user says: deep dive, deep-dive, investigate deeply, trace and interview.
argument-hint
<problem or exploration target>

Deep Dive

Orchestrates a 2-stage pipeline: first investigate WHY something happened (trace), then define WHAT to do about it (deep-interview). Trace findings feed into the interview via 3-point injection.

Pipeline

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

When to Use

  • User has a problem but doesn't know the root cause
  • Bug investigation: "Something broke and I need to figure out why"
  • Feature exploration: "I want to improve X but first need to understand it"

When NOT to Use

  • Already know the root cause → use /deep-interview
  • Clear specific request → execute directly
  • Investigation only, no requirements → use /trace

Phases

Phase 1: Initialize
  1. Parse problem, detect brownfield/greenfield
  2. Generate 3 trace lane hypotheses (code-path, config/env, measurement/artifact)
Phase 2: Lane Confirmation

Present hypotheses to user for confirmation (1 round).

Phase 3: Trace Execution

Run 3 parallel tracer lanes using @tracer agents:

  • Each lane: evidence for, evidence against, critical unknown, discriminating probe
  • Rebuttal round between top hypotheses
  • Convergence detection
  • Save to .omc/specs/deep-dive-trace-{slug}.md
Phase 4: Interview with Trace Injection

Follow deep-interview protocol with 3 overrides:

  1. initial_idea enrichment: Include trace's most likely explanation
  2. codebase_context replacement: Use trace synthesis (skip re-exploration)
  3. question queue injection: Per-lane critical unknowns become first questions

Low-confidence trace: don't inject uncertain conclusion, use ALL unknowns as questions.

Phase 5: Execution Bridge

Same options as deep-interview: ralplan → omg-autopilot (recommended), omg-autopilot, ralph, team, or refine further.

Output

Spec saved to .omc/specs/deep-dive-{slug}.md with additional "Trace Findings" section.

© 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-dive 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 Dive 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 Dive compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Deep Dive this skillzereight/gitlab-mcp2k1 repos~536Automated safety check: PassMIT
Root Cause Investigationgarrytan/gstack136k—~12kAutomated safety check: NotesMIT
Observe Traceruvnet/ruflo74k—~522Automated safety check: NotesMIT
Investigate CIClickHouse/ClickHouse50k—~11kAutomated safety check: NotesApache-2.0
Investigate Issuevideojs/video.js40k—~318Automated safety check: PassCustom licence
Distributed Tracingwshobson/agents40k12 repos~527Automated safety check: PassMIT

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Questions about Deep Dive

What does Deep Dive do?

2-stage pipeline: trace (causal investigation) then deep-interview (requirements). Deep Dive is an agent skill from zereight/gitlab-mcp. 2-stage pipeline: trace (causal investigation) then deep-interview (requirements).

When should I use Deep Dive?

Deep Dive fits situations like: says: deep dive; investigate deeply; trace and interview.

How do I install Deep Dive in Claude Code?

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

How do I install Deep Dive in Codex?

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

Can I use Deep Dive 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-dive -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-dive, .gemini/skills/deep-dive, .github/skills/deep-dive and .opencode/skills/deep-dive in your project.

What does Deep Dive need to run?

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

Does Deep Dive 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 Dive 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 Dive use?

Deep Dive 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 Dive use?

About 536 tokens (SKILL.md is roughly 2.1k 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 Dive?

Skills that share tags, products or a category with Deep Dive: Root Cause Investigation (garrytan/gstack, 136k stars), Observe Trace (ruvnet/ruflo, 74k stars), Investigate CI (ClickHouse/ClickHouse, 50k stars) and Investigate Issue (videojs/video.js, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deep Dive?

zereight (a GitHub user) maintains it in zereight/gitlab-mcp, which has 2,029 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.