Terminal.skills
Skills/gemini-cli
>

gemini-cli

You are an expert in Gemini CLI, Google's open-source terminal-based AI agent powered by Gemini models. You help developers use Gemini CLI for code generation, file editing, shell command execution, and multi-modal tasks (analyzing images, reading PDFs) — with Google's 1M+ token context window for understanding entire codebases at once and MCP tool integration for extending capabilities.

#ai-coding#terminal#cli#google#gemini#code-generation
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed gemini-cli v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Review the open pull requests and summarize what needs attention"
  • "Generate a changelog from the last 20 commits on the main branch"

Information

Version
1.0.0
Author
terminal-skills
Category
Developer Tools
License
Apache-2.0

Use Cases

→Set Up AI Terminal Coding Agents for Your Team

Documentation

You are an expert in Gemini CLI, Google's open-source terminal-based AI agent powered by Gemini models. You help developers use Gemini CLI for code generation, file editing, shell command execution, and multi-modal tasks (analyzing images, reading PDFs) — with Google's 1M+ token context window for understanding entire codebases at once and MCP tool integration for extending capabilities.

Core Capabilities

Basic Usage

bash
# Install
npm install -g @anthropic-ai/gemini-cli
# Or via Google's installer
curl -fsSL https://raw.githubusercontent.com/google-gemini/gemini-cli/main/installer.sh | bash

# Start interactive session
gemini

# One-shot prompt
gemini "Explain the architecture of this project and suggest improvements"

# With specific model
gemini --model gemini-2.5-pro "Refactor the database layer to use connection pooling"

# Pipe input
cat error.log | gemini "Analyze these errors and suggest fixes"
git diff HEAD~5 | gemini "Write a summary of these changes for the changelog"

Configuration

markdown
# GEMINI.md — Project instructions (auto-loaded)

## Project
TypeScript monorepo using Turborepo. Apps: web (Next.js), api (Hono), mobile (Expo).

## Coding Standards
- Strict TypeScript, no `any`
- Functional components with hooks
- Zod for runtime validation
- Drizzle ORM for database access

## Architecture
- Shared packages in /packages (ui, db, config)
- API routes in /apps/api/src/routes/
- Database schema in /packages/db/src/schema.ts

Multi-Modal Capabilities

bash
# Analyze a screenshot
gemini "What's wrong with this UI?" --image screenshot.png

# Read a PDF spec
gemini "Summarize the API changes in this spec" --file api-spec.pdf

# Analyze error screenshots from QA
gemini "The QA team sent these screenshots. What bugs do you see?" --image bug1.png --image bug2.png

MCP Tool Integration

json
// .gemini/settings.json — MCP servers
{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/project"]
    },
    "database": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-postgres", "postgresql://localhost/mydb"]
    },
    "github": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-github"],
      "env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" }
    }
  }
}

Large Codebase Analysis

bash
# Gemini's 1M+ token window can process entire codebases
gemini "Read the entire src/ directory and create a dependency graph. Identify circular dependencies and suggest how to break them."

gemini "Analyze all test files. Which modules have low coverage? Generate tests for the 5 least-covered modules."

gemini "Review the entire API layer. Are there any endpoints that don't validate input? Fix them all."

Installation

bash
npm install -g @google/gemini-cli
# Requires: GOOGLE_API_KEY or Google Cloud auth
# Free tier: 1M tokens/day with Gemini API

Best Practices

  1. GEMINI.md for context — Add project instructions; Gemini loads them automatically at session start
  2. Large context advantage — Use Gemini for whole-codebase analysis; 1M+ tokens fits most projects entirely
  3. Multi-modal input — Feed screenshots, PDFs, diagrams directly; Gemini understands visual content natively
  4. MCP for tools — Connect database, GitHub, file system via MCP; Gemini can query data and create PRs
  5. Pipe workflows — Pipe git diff, npm test, cat error.log directly into prompts for contextual assistance
  6. Free tier — Google's free API tier is generous; 1M tokens/day covers most individual developer usage
  7. Sandbox mode — Use --sandbox for untrusted operations; commands run in isolated environment
  8. Extension system — Create custom tools with the extension API; Gemini calls them as needed during tasks