# Scout

> Map unfamiliar code or research an approach before planning, read-only and fast.

- Skill: `toruai/scout` (Agent Skill)
- Install (CLI): `npx skillmds add toruai/scout`
- Raw SKILL.md: https://api.skillmd.com/api/skills/toruai/scout/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: ToruAI (https://skillmd.com/u/toruai)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/toruai/scout

---


# Scout - Quick Exploration

Delegate exploration tasks to the Scout agent (haiku model - fast & cheap).

## Usage

```
/scout how does authentication work here?
/scout where is the database schema defined?
/scout what options do we have for caching?
/scout                    # will ask what to explore
```

## Process

1. If no question provided, ask: "What do you want to explore?"

2. Delegate to Scout agent:
```
"Scout, explore: [question]

Context:
- Project: [current directory/project name]
- Relevant area: [if obvious from question]

Return:
- What you found
- How it works
- Options (if applicable)
- Unknowns or questions for the user"
```

3. Present Scout's findings to the user

4. Ask: "Want me to dig deeper on anything?"

## When to Use

- "How does X work in this codebase?"
- "Where is Y implemented?"
- "What are our options for Z?"
- "Find all places that do X"
- Before starting work on unfamiliar area
- Quick research on approaches

## Scout's Strengths

- Fast (haiku model)
- Systematic (follows code paths, checks tests, looks at git history)
- Evidence-based (cites files and line numbers)
- Surfaces unknowns (doesn't hide gaps)

## Examples

**Exploring a feature:**
```
/scout how does the scraper handle rate limiting?
```

**Finding implementations:**
```
/scout where are all the API endpoints defined?
```

**Researching options:**
```
/scout what libraries could we use for PDF generation?
```

**Understanding patterns:**
```
/scout what's the error handling pattern in this codebase?
```