How do I install the Deployer Training skill?

Run npx skillmds@latest add tomevault-io/deployer-training in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Deployer Training safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Deployer Training?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Deployer Training free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Deployer Training?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Deployer Training by tomevault-io — Agent Skill

Name: Deployer Training
Author: tomevault-io

Deployer Training

Generate comprehensive deployer and developer training documentation by scanning a codebase. Use when user asks for onboarding guides, developer documentation, system overviews, or needs to understand a new codebase. Triggers on phrases like "create training materials", "generate developer guide", "explain this codebase", "onboarding documentation", or "deployer manual". Use when this capability is needed.

tomevault-io 76732db 2 files · 3.7 KB Updated Sep 17, 2026

File contents

Deployer Training Materials Generator

Generate comprehensive, production-quality training documentation by scanning and analyzing a codebase using Gemini AI.

When to Use

Creating onboarding documentation for new developers
Generating deployer guides for operations teams
Understanding a new or unfamiliar codebase
Documenting a product before release
EU AI Act Articles 13 & 14 compliance (Transparency & Human Oversight)

Quick Start

python scripts/generate_training.py --path /path/to/repo

Instructions

Identify the target codebase: Determine the repository root to scan.

Run the generator:

python "AI Act skills packages/AI Act package/deployer-training/scripts/generate_training.py" \
  --path <path-to-repository> \
  --name "Your Product Name"

Review the output: Check project root Output/Deployer_Guide.md for the generated documentation.
Human review: Always recommend human review for accuracy and completeness.

What You Get

A comprehensive Deployer_Guide.md with:

Executive Summary: High-level product overview.
System Architecture: Component diagrams (Mermaid), data flow, tech stack.
Product Capabilities: Core features, user journeys, configuration options.
Developer Onboarding: Environment setup, extension patterns, testing guidelines.
Operational Guide: Deployment strategy, troubleshooting & limitations.

Parameters

Parameter	Type	Default	Description
`--path`	string	`.`	Path to the repository root
`--output`	string	`Deployer_Guide.md`	Output file path
`--model`	string	Auto	Specific model (uses `gemini-3-pro-preview` then `gemini-2.0-flash-exp` as fallback)

Requirements

Python 3.8+
google-genai package: pip install google-genai
GEMINI_API_KEY environment variable set

Best Practices

Run on a clean checkout of the repository.
The generator respects .gitignore and excludes .env files for security.
For large codebases, review the "Total context size" output to ensure it fits in the model's context window.
Always perform human review on generated documentation.

EU AI Act Compliance

This tool addresses:

Article 13: Transparency and provision of information to users
Article 14: Human oversight requirements (documentation for deployers)

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: deployer-trainingdescription: Generate comprehensive deployer and developer training documentation by scanning a codebase. Use when user asks for onboarding guides, developer documentation, system overviews, or needs to understand a new codebase. Triggers on phrases like "create training materials", "generate developer guide", "explain this codebase", "onboarding documentation", or "deployer manual". Use when this capability is needed.---# Deployer Training Materials GeneratorGenerate comprehensive, production-quality training documentation by scanning and analyzing a codebase using Gemini AI.## When to Use- Creating onboarding documentation for new developers- Generating deployer guides for operations teams- Understanding a new or unfamiliar codebase- Documenting a product before release- EU AI Act Articles 13 & 14 compliance (Transparency & Human Oversight)## Quick Start```bashpython scripts/generate_training.py --path /path/to/repo```## Instructions1. **Identify the target codebase**: Determine the repository root to scan.2. **Run the generator**: ```bash python "AI Act skills packages/AI Act package/deployer-training/scripts/generate_training.py" \ --path <path-to-repository> \ --name "Your Product Name" ```3. **Review the output**: Check project root `Output/Deployer_Guide.md` for the generated documentation.4. **Human review**: Always recommend human review for accuracy and completeness.## What You GetA comprehensive `Deployer_Guide.md` with:1. **Executive Summary**: High-level product overview.2. **System Architecture**: Component diagrams (Mermaid), data flow, tech stack.3. **Product Capabilities**: Core features, user journeys, configuration options.4. **Developer Onboarding**: Environment setup, extension patterns, testing guidelines.5. **Operational Guide**: Deployment strategy, troubleshooting & limitations.## Parameters| Parameter | Type | Default | Description ||-----------|------|---------|-------------|| `--path` | string | `.` | Path to the repository root || `--output` | string | `Deployer_Guide.md` | Output file path || `--model` | string | Auto | Specific model (uses `gemini-3-pro-preview` then `gemini-2.0-flash-exp` as fallback) |## Requirements- Python 3.8+- `google-genai` package: `pip install google-genai`- `GEMINI_API_KEY` environment variable set## Best Practices- Run on a clean checkout of the repository.- The generator respects `.gitignore` and excludes `.env` files for security.- For large codebases, review the "Total context size" output to ensure it fits in the model's context window.- Always perform human review on generated documentation.## EU AI Act ComplianceThis tool addresses:- **Article 13**: Transparency and provision of information to users- **Article 14**: Human oversight requirements (documentation for deployers)---> Converted and distributed by [TomeVault](https://tomevault.io/claim/dtmc-marketplace) — claim your Tome and manage your conversions.

Frequently asked questions