From first prompt to production workflows — 18 modules covering setup, SDLC, MCP integration, Google Cloud, GitHub Actions, and Google Workspace automation.
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Gemini CLI is Google's open-source AI agent for your terminal. It brings Gemini 2.5 Pro/Flash directly to your shell — reading files, running commands, calling MCP servers, and automating your entire development workflow. Unlike web chat, it operates in your project context: it can see your code, run tests, commit to Git, and trigger CI pipelines. The free tier includes 60 requests per minute and 1,000 requests per day using Gemini 2.5 Pro — the most capable model available in any free AI CLI tool.
@file mentions.GEMINI_API_KEY in your environment to switch to the paid API.
Windows-first setup: Node.js via WinGet, execution policy fix, global npm install. Google OAuth login flow. First commands: file analysis, code generation, shell execution. Free tier limits and rate-limit behavior.
@file and @folder mentions to load context. Built-in /slash commands reference. Memory system (/memory add, /memory show). Multiline input with triple-backtick blocks. Effective prompting patterns for code tasks.
The project context file that loads every session. Model selection (Flash vs Pro), temperature, system instructions, token caching. Global vs project-level config. Three starter templates: API project, monorepo, data pipeline.
The .gemini/skills/ directory. Writing reusable skill.md files with argument placeholders. Sharing skills across projects. Building a personal skill library: PR summarizer, test generator, release notes writer.
Planning vs execution separation: use Plan Mode before destructive or multi-step operations. How Gemini routes to the best model for planning. Approval gates: inspect, edit, and approve plans before they execute. Integrating Plan Mode into team workflows.
Use Gemini CLI as a requirements critic: PRD generation, user story decomposition, INVEST scoring. Feed existing docs via @file for gap analysis. Output machine-readable specs for downstream modules.
System design conversations with full codebase context. Mermaid diagram generation (sequence, ER, C4). API contract drafting with OpenAPI 3.1. Database schema design with migration scripts. Architecture decision records (ADR) from a prompt.
Scaffold full projects from a spec file. Multi-file context: load entire src/ trees, generate code that fits the existing patterns. Commit message generation from staged diffs. Branch-per-feature workflow with Gemini as co-author.
Generate unit tests from implementation files: happy path, edge cases, error branches. Feed test failure output back to Gemini for diagnosis. Coverage gap analysis from lcov reports. Mutation testing prompts to verify test quality.
Generate Dockerfiles, multi-stage builds, and docker-compose from project structure. CI YAML generation for GitHub Actions and Cloud Build. Runbook authoring from architecture docs. Log analysis: paste error output, get root cause and fix.
Gemini CLI's native MCP support: add any MCP server in GEMINI.md. FastMCP server development. OAuth 2.0 for remote servers. Google's official partner extensions (Maps, YouTube, Search). Build a custom MCP server and connect it to Gemini in one session.
Install community extensions from geminicli.com. Write your own extension: manifest, capabilities, distribution. Publish to the gallery. Differences between extensions and MCP servers: when to use which. Extension sandboxing and permissions.
Automate PR review with the @gemini-cli trigger in PR comments. Issue triage and labeling workflows. Action YAML: headless mode, output parsing, conditional steps. Security: OIDC auth instead of long-lived tokens.
100+ agent skills for Gmail, Google Docs, Drive, and Sheets via the official Workspace extension. OAuth flow for Workspace APIs. Real workflows: summarize email threads, generate Docs from specs, update Sheets from code output, organize Drive folders.
Official MCP servers for BigQuery, Cloud Storage, Cloud Run, Pub/Sub, and Spanner. Natural language → SQL on your data warehouse. ADC authentication, minimum-privilege IAM setup, and compound workflows that orchestrate multiple Google Cloud services in a single Gemini prompt.
Non-interactive mode with the gemini -p "prompt" flag. --output-format json for machine-readable output. --yolo for fully unattended runs. Full pipeline integration: trigger from GitHub Actions, parse JSON responses, branch on results.
/memory add for persistent session facts. /restore to resume from a saved checkpoint. Global vs project memory scope. Branching memory: keep multiple working contexts for different features. Memory export for handoff to teammates.
Combine Gemini CLI with PowerShell and bash scripts. --sandbox flag with Docker for safe code execution. Automation scripts: daily standup generator, weekly PR digest, release pipeline assistant. Cross-platform script patterns (Windows + Linux parity).
Start with a one-paragraph product brief. Use Gemini CLI to: generate a PRD, decompose into user stories, produce a system design with Mermaid diagrams, scaffold the implementation, generate and run tests, write the Dockerfile and CI YAML, open a PR, and trigger automated PR review — all from your terminal. Both Windows PowerShell and bash paths shown side-by-side.
Everything Windows developers need: execution policy explained (RemoteSigned vs Bypass vs Unrestricted), WinGet vs chocolatey vs manual Node.js install, Windows Terminal profiles for color-coded Gemini sessions, WSL2 setup for Linux parity, PATH troubleshooting for global npm packages, Docker Desktop configuration for the --sandbox flag, and a lookup table of the 15 most common Windows-specific errors with fixes.
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This track is beginner-friendly from Module 01. For Track 4 (MCP Servers) and the Capstone, basic shell comfort and Node.js familiarity are helpful. You do not need to know Python or the Gemini API to start.