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.
npx skills add VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill deep-geminigit clone --depth 1 https://github.com/VCnoC/Claude-Code-Zen-mcp-Skill-WorkWrote 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.
[](https://agentmods.dev/skills/vcnoc/claude-code-zen-mcp-skill-work/deep-gemini)<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="Measured on agentmods" height="20"></a>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 | $0.00058 | $0.03125 |
| Sonnet 5 | $0.00023 | $0.01250 |
| Haiku 4.5 | $0.00012 | $0.00625 |
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 8d 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.
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
geminicommand 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
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.
- 8d ago First seen · 836 lines · 116 tokens per session scan A d01be7d2b680
deep-gemini is a skill published in the GitHub repository VCnoC/Claude-Code-Zen-mcp-Skill-Work (116 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 116 tokens to every session and 6,251 once invoked, about $0.0006 per session on Opus 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.
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