research

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Structure

• Ships 1 executable scriptscripts/research.sh. Review what they do before enabling the skill for agents with tool access.
• No license declaredConfirm you may reuse this skill before importing it into your repository.
• The source hub's security checks flagged this skillGen Agent Trust Hub: warn (This research skill uses the Tavily API to perform web searches. It includes an automated authentication flow that uses npx to download and execute remote code and scans local directories for stored credentials.); Snyk: warn (Risk: MEDIUM · No issues)

SKILL.md

---
name: research  
description: "Comprehensive research grounded in web data with explicit citations. Use when you need multi-source synthesis—comparisons, current events, market analysis, detailed reports. "
---
# Research Skill

Conduct comprehensive research on any topic with automatic source gathering, analysis, and response generation with citations.

## Authentication

The script uses OAuth via the Tavily MCP server. **No manual setup required** - on first run, it will:
1. Check for existing tokens in `~/.mcp-auth/`
2. If none found, automatically open your browser for OAuth authentication

> **Note:** You must have an existing Tavily account. The OAuth flow only supports login — account creation is not available through this flow. [Sign up at tavily.com](https://tavily.com) first if you don't have an account.

### Alternative: API Key

If you prefer using an API key, get one at https://tavily.com and add to `~/.claude/settings.json`:
```json
{
  "env": {
    "TAVILY_API_KEY": "tvly-your-api-key-here"
  }
}
```

## Quick Start

> **Tip**: Research can take 30-120 seconds. Press **Ctrl+B** to run in the background.

### Using the Script

```bash
./scripts/research.sh '<json>' [output_file]
```

**Examples:**

```bash
# Basic research
./scripts/research.sh '{"input": "quantum computing trends"}'

# With pro model for comprehensive analysis
./scripts/research.sh '{"input": "AI agents comparison", "model": "pro"}'

# Save to file
./scripts/research.sh '{"input": "market analysis for EVs", "model": "pro"}' ./ev-report.md

# Quick targeted research
./scripts/research.sh '{"input": "climate change impacts", "model": "mini"}'
```

## Parameters

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `input` | string | Required | Research topic or question |
| `model` | string | `"mini"` | Model: `mini`, `pro`, `auto` |

## Model Selection

**Rule of thumb**: "what does X do?" -> mini. "X vs Y vs Z" or "best way to..." -> pro.

| Model | Use Case | Speed |
|-------|----------|-------|
| `mini` | Single topic, targeted research | ~30s |
| `pro` | Comprehensive multi-angle analysis | ~60-120s |
| `auto` | API chooses based on complexity | Varies |

## Examples

### Quick Overview

```bash
./scripts/research.sh '{"input": "What is retrieval augmented generation?", "model": "mini"}'
```

### Technical Comparison

```bash
./scripts/research.sh '{"input": "LangGraph vs CrewAI for multi-agent systems", "model": "pro"}'
```

### Market Research

```bash
./scripts/research.sh '{"input": "Fintech startup landscape 2025", "model": "pro"}' fintech-report.md
```