Gemini CLI

Table of Contents

• •Overview
• •When to Use This Skill
• •Core Command Pattern
• •Model Selection
• •Command Patterns
• •Prompt Engineering for Gemini
• •Common Use Cases
• •Combining Claude + Gemini
• •Advanced Patterns
• •Error Handling
• •Quick Reference

Overview

Execute tasks using Google's gemini command-line tool to leverage Gemini 2.5 Pro alongside Claude. This skill enables headless (non-interactive) execution where content is piped to Gemini, processed with custom prompts, and results are saved directly to files.

When to Use This Skill

Invoke this skill when:

• •Alternative perspective: Get Gemini's viewpoint on a problem Claude is solving
• •Parallel analysis: Run Claude and Gemini analysis side-by-side for comparison
• •Specific Gemini strengths: Leverage capabilities where Gemini excels
• •Headless processing: Need non-interactive AI execution that saves to files
• •Batch processing: Process multiple inputs through Gemini
• •Second opinion: Validate Claude's analysis with Gemini's assessment

When NOT to use: Tasks Claude can handle directly without needing a second AI perspective.

Core Command Pattern

The fundamental pattern for using gemini CLI:

cat [input-files] | gemini "[PROMPT]" --model gemini-2.5-pro > [output-file]

Components:

1. •cat [input-files] - Concatenate input content (optional if prompt-only)
2. •| gemini "[PROMPT]" - Pipe to gemini with custom instructions
3. •--model gemini-2.5-pro - Specify the model
4. •> [output-file] - Redirect output to a file

Model Selection

Specify with: --model gemini-2.5-pro or --model gemini-2.5-flash

Command Patterns

Single File Input

cat document.md | gemini "Summarize in 3 bullet points" --model gemini-2.5-pro > summary.md

Multiple File Input

cat file1.txt file2.txt | gemini "Find common themes" --model gemini-2.5-pro > themes.md

Prompt-Only (No Input)

gemini "Create a 10-item code review checklist" --model gemini-2.5-pro > checklist.md

Prompt Engineering for Gemini

Define Role and Task

gemini "You are an expert [ROLE]. [TASK]. Format as [FORMAT]." --model gemini-2.5-pro

Multi-Part Instructions

gemini "Task:
1. [First step]
2. [Second step]
3. [Third step]

Format: Markdown with headings" --model gemini-2.5-pro

Common Use Cases

Alternative Perspective

Get Gemini's viewpoint alongside Claude's:

cat analysis.md | gemini "Review this analysis. Identify gaps or alternative viewpoints." --model gemini-2.5-pro > gemini_perspective.md

Verify output: head -20 gemini_perspective.md to confirm format matches expectations.

Comparative Analysis

Compare two approaches:

cat approach_a.md approach_b.md | gemini "Compare these approaches. Create pros/cons table, recommend when to use each." --model gemini-2.5-pro > comparison.md

Verify output: Check comparison.md contains expected table structure.

Code Review

Review code with Gemini:

cat code_file.py | gemini "Review for: 1) Design patterns, 2) Potential issues, 3) Security concerns. Provide specific examples." --model gemini-2.5-pro > code_review.md

Sample Output (code_review.md):

## Code Review

### Design Patterns: 7/10
- Uses functional approach appropriately
- Consider adding type hints

### Potential Issues
1. No input validation on line 15
2. Missing error handling for empty lists

### Security Concerns
- None identified for this scope

Verify output: grep "##" code_review.md to confirm sections exist.

Research Synthesis

Synthesize multiple sources:

cat source1.md source2.md source3.md | gemini "Synthesize key insights. Create executive summary followed by detailed findings." --model gemini-2.5-pro > synthesis.md

Batch Processing

Process multiple files:

for file in *.md; do
  cat "$file" | gemini "Summarize this document" --model gemini-2.5-flash > "summaries/${file%.md}_summary.md"
done

Combining Claude + Gemini

Sequential Processing

Claude processes first, Gemini refines:

1. •Claude creates initial analysis, saves to file
2. •Gemini reviews and enhances, saves refinement
3. •Compare both results

Parallel Analysis

Both analyze the same input:

1. •Claude analyzes in conversation
2. •Gemini analyzes same content, saves to file
3. •Compare perspectives, synthesize insights

Division of Labor

• •Claude: Interactive exploration, code generation
• •Gemini: Batch processing, alternative perspectives

Advanced Patterns

Iterative Refinement

# First pass
cat input.md | gemini "Analyze..." --model gemini-2.5-pro > v1.md

# Second pass with feedback
cat v1.md | gemini "Review and improve this analysis..." --model gemini-2.5-pro > v2.md

Chaining with CLI Tools

cat document.md | gemini "Extract key points" --model gemini-2.5-pro | grep "##" > headings.txt

Environment Variables for Reusable Prompts

PROMPT="Analyze for security vulnerabilities. Format as Markdown."
cat code.py | gemini "$PROMPT" --model gemini-2.5-pro > security_review.md

Error Handling

If command fails:

1. •Verify gemini CLI is installed: which gemini
2. •Check file paths exist: ls -la input.md
3. •Ensure prompt is properly quoted
4. •Verify model flag: --model gemini-2.5-pro

If output is poor:

1. •Make prompt more specific
2. •Add role definition
3. •Request structured format
4. •Try gemini-2.5-pro instead of flash

Quote escaping:

gemini 'Say "Hello World"' --model gemini-2.5-pro

Quick Reference

Prompt Template:

"You are [ROLE].
Task: [WHAT TO DO]
Input: [WHAT YOU'RE ANALYZING]
Output: [DESIRED FORMAT]
Context: [CONSTRAINTS/AUDIENCE]"

Best Practices:

1. •Always specify model with --model
2. •Define role in prompt
3. •Request structured output format
4. •Use descriptive output filenames
5. •Verify output with head or grep after generation