/google-ai-mode-skill

name: google-ai-mode-skill
description: Use this skill when the user requests current information, documentation, coding examples, or web research beyond the knowledge cutoff. Queries Google's AI Search mode to retrieve comprehensive AI-generated overviews with source citations from 100+ websites. Returns markdown with inline footnoted references [1][2][3]. You will receive a detailed Markdown file with references and information summarized directly from Google's AI search. Ideal for you to get new information and clues for further research.

Google AI Mode Skill

Query Google's AI Search mode to retrieve comprehensive, source-grounded answers from across the web.

When to Use This Skill

Trigger this skill when the user:

• Requests current information beyond the knowledge cutoff (post-January 2025)
• Needs documentation or API references for libraries and frameworks
• Asks for coding examples or implementation patterns
• Wants technical comparisons or best practices
• Requires research with citations and sources
• Mentions "Google AI search", "Google AI mode", or "web research"

CLI Flags

Essential Flags

**`--debug`** - Enable comprehensive logging

python scripts/run.py search.py --query "..." --debug

• Saves detailed logs to `logs/search_YYYY-MM-DD_HH-MM-SS.log`
• Logs every step: browser launch, CAPTCHA detection, AI content waiting, citation extraction
• Essential for troubleshooting CAPTCHA issues or failed searches
• Log file path printed at completion

**`--save`** - Save results to skill folder

python scripts/run.py search.py --query "..." --save

• Saves markdown to `results/YYYY-MM-DD_HH-MM-SS_Query_Name.md`
• Timestamped filename for organized storage
• Results preserved in skill directory for future reference
• Use instead of `--output` for automatic naming

**Combined usage** (recommended for debugging):

python scripts/run.py search.py --query "..." --debug --save

Other Flags

**`--show-browser`** - Show browser window (for CAPTCHA solving)

python scripts/run.py search.py --query "..." --show-browser

**`--output <path>`** - Custom output file path

python scripts/run.py search.py --query "..." --output result.md

**`--json`** - Include JSON metadata in output

python scripts/run.py search.py --query "..." --output result.md --json

Query Optimization Strategy

**CRITICAL**: Always optimize user queries before execution. Google AI Mode's quality depends on query precision.

Optimization Template

[Technology/Topic] [Version] [Year] ([Specific Aspect 1], [Aspect 2], [Aspect 3]). [Output format request].

Optimization Rules

1. **Include Current Year (2026)** for up-to-date results 2. **Use parentheses** to list specific aspects needed 3. **Request structured output** (tables, comparisons, categorized lists) 4. **Include version numbers** for library/framework queries

Examples

| User Query | Optimized Query | |-----------|----------------| | "React hooks" | "React hooks best practices 2026 (useState, useEffect, custom hooks, common pitfalls). Provide code examples." | | "What's new in Rust?" | "Rust 1.75 new features 2026 (async traits, impl Trait improvements, const generics, stabilized APIs). Include migration guide and code examples." | | "PostgreSQL vs MySQL performance?" | "PostgreSQL vs MySQL performance comparison 2026 (query optimization, indexing strategies, concurrent writes, JSON handling, scaling patterns). Provide benchmark data and use case recommendations." | | "How to handle errors in Go?" | "Go error handling patterns 2026 (error wrapping, custom errors, sentinel errors, panic vs error, testing error cases). Provide code examples and best practices comparison." | | "Learn FastAPI basics" | "FastAPI tutorial 2026 (routing, dependency injection, async endpoints, request validation with Pydantic, OpenAPI documentation, testing). Include step-by-step implementation guide." |

**Note:** If user provides an already detailed query with version numbers and requirements, use it as-is.

Workflow

1. Receive user request 2. Optimize query using template above 3. Inform user: "Searching for: '[optimized query]'" 4. Execute search with `--save --debug` flags 5. Return results with inline citations [1][2][3]

Script Execution

**CRITICAL**: Always use the `run.py` wrapper. Direct script execution will fail.

Basic Search

python scripts/run.py search.py --query "Your search query"

Recommended Usage

python scripts/run.py search.py --query "..." --save --debug

The `run.py` wrapper automatically:

• Creates `.venv` on first run
• Installs dependencies (patchright, beautifulsoup4, html-to-markdown)
• Activates virtual environment
• Executes search script
• Installs Google Chrome (not Chromium) for anti-detection

How It Works

1. **Persistent Browser Context**: Uses saved browser profile at `~/.cache/google-ai-mode-skill/chrome_profile` to preserve cookies/session between searches 2. **Eliminates CAPTCHAs**: Persistent context means Google recognizes the browser → rarely triggers CAPTCHA 3. **AI Content Detection**: Waits for Google AI Overview to appear on page 4. **Citation Extraction**: Injects JavaScript to extract source links from AI response 5. **Markdown Conversion**: Converts HTML to markdown with inline citations [1][2][3] 6. **Fast Results**: Typical search completes in 5-7 seconds (no CAPTCHA)

CAPTCHA Handling

**With persistent context, CAPTCHAs are rare.** If encountered:

1. **Detection**: Multi-layer check (URL `/sorry/index`, page text, content length) 2. **Automatic Handling**: If CAPTCHA detected in headless mode → script returns `CAPTCHA_REQUIRED` error 3. **Manual Solution**: Re-run with `--show-browser` flag, solve CAPTCHA in browser, script continues automatically

**Note**: After CAPTCHA is solved once, persistent context preserves the session → future searches won't require CAPTCHA.

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