A two-step workflow for deeply analysing code and turning the findings into structured technical documents. It uses Gemini CLI for code and architecture analysis, then generates documentation that includes Big O explanations of performance.

Use it to explain code logic, software architecture, and performance. It can help produce structured technical documents for complex projects.

It reduces the manual work of understanding complex code before documenting it. It also helps keep analysis and documentation as separate, reviewable stages.

deep-gemini — Skill for Claude Code and Codex by VCnoC

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill deep-gemini

Clone the repo

git clone --depth 1 https://github.com/VCnoC/Claude-Code-Zen-mcp-Skill-Work

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini/github.svg)](https://agentmods.dev/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini)

Your own site

<a href="https://agentmods.dev/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini"><img src="https://agentmods.dev/badge/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini"><img src="https://agentmods.dev/badge/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 116 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 6,251 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00116	$0.06251
Opus 5.5	$0.00046	$0.02500
Sonnet 5.5	$0.00023	$0.01250
Haiku 4.5	$0.00012	$0.00625

Measured 2mo ago against content hash d01be7d2b680, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deep-gemini scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/deep-gemini/SKILL.md · 836 lines

How it starts

The opening of the file, as written. The whole thing — 836 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deep Gemini - Deep Technical Documentation Generation

Overview

This skill provides a two-stage deep analysis and documentation workflow:

Stage 1 - Analysis (clink): Launch gemini CLI in WSL to perform deep code/architecture/performance analysis Stage 2 - Documentation (docgen): Generate structured technical documents with Big O complexity analysis

All operations leverage zen-mcp's workflow tools to ensure thorough analysis and professional documentation output.

Technical Architecture:

zen-mcp clink: Bridge tool to launch gemini CLI in WSL environment for code analysis
zen-mcp docgen: WorkflowTool for multi-step structured document generation with complexity analysis
gemini CLI session: Opened via gemini command in WSL, where deep analysis is executed
Main Claude Model: Context gathering, workflow orchestration, user interaction
User: Provides analysis targets, reviews final documents

Two-Stage Workflow:

Main Claude → clink → Gemini CLI (Analysis) → docgen → Structured Doc → User
     ↑                                                                  ↓
     └──────────────────── User Approval ──────────────────────────────┘

Division of Responsibilities:

Stage 1 (Analysis via clink):

Gemini CLI Session (in WSL): Deep code/architecture/performance analysis, pattern identification
clink tool: Bridges Zen MCP requests to CLI-executable commands, captures CLI output and metadata

Stage 2 (Documentation via docgen):

docgen tool: Receives analysis results, executes multi-step document generation workflow, adds Big O complexity analysis
Main Claude Model: Orchestrates both stages, manages user approvals, saves final documents

When to Use This Skill

Trigger this skill when the user requests:

"Use gemini to deeply analyze code logic"
"Generate architecture analysis document"
"Analyze performance bottlenecks and generate report"
"Deeply understand this code and generate documentation"
"Generate model architecture analysis"
"Use gemini for deep analysis"
Any request requiring deep technical understanding and analysis documentation

Read the full file on GitHub · 836 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 836 lines · 116 tokens per session scan A d01be7d2b680

Subscribe to this mod's changes

deep-gemini is a skill published in the GitHub repository VCnoC/Claude-Code-Zen-mcp-Skill-Work (118 stars, last pushed 10mo ago), licensed Apache-2.0. It adds 116 tokens to every session and 6,251 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Building agents Writing and docs

deep-gemini next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
deep-geminiVCnoC/Claude-Code-Zen-mcp-Skill-Work	Skill	118	10mo ago	Apache-2.0	A	116	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code