google-ai-mode-skill

# 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
```bash
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
```bash
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):
```bash
python scripts/run.py search.py --query "..." --debug --save
```

### Other Flags

**`--show-browser`** - Show browser window (for CAPTCHA solving)
```bash
python scripts/run.py search.py --query "..." --show-browser
```

**`--output <path>`** - Custom output file path
```bash
python scripts/run.py search.py --query "..." --output result.md
```

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

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

### Recommended Usage

```bash
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.

## Output Format

Returns markdown with inline citations and source list. Example:

```markdown
React 18 introduces concurrent features including Suspense for data fetching[1],
automatic batching for state updates[2], and transitions for non-urgent updates[3].

---

## Sources:

[1] React 18 Release Notes
https://react.dev/blog/2022/03/29/react-v18

[2] Automatic Batching Explained
https://github.com/reactwg/react-18/discussions/21

[3] Transitions API Documentation
https://react.dev/reference/react/useTransition
```

## Common Use Cases

### Finding Li