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Use when starting reverse engineering on an unfamiliar codebase to identify layers, patterns, and structure before detailed analysis

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
9
Hot score
84
Updated
March 20, 2026
Overall rating
C1.3
Composite score
1.3
Best-practice grade
A92.0

Install command

npx @skill-hub/cli install cliftonc-unwind-start

Repository

cliftonc/unwind

Skill path: skills/start

Use when starting reverse engineering on an unfamiliar codebase to identify layers, patterns, and structure before detailed analysis

Open repository

Best for

Primary workflow: Ship Full Stack.

Technical facets: Full Stack.

Target audience: everyone.

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: cliftonc.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install start into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/cliftonc/unwind before adding start to shared team environments
  • Use start for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

Original source / Raw SKILL.md

---
name: start
description: Use when starting reverse engineering on an unfamiliar codebase to identify layers, patterns, and structure before detailed analysis
allowed-tools:
  - Read
  - Grep
  - Glob
  - Bash(git:*, mkdir:*, ls:*)
  - Write(docs/unwind/**)
  - Edit(docs/unwind/**)
---

# Discovering Architecture

## Overview

Dispatch a subagent to systematically explore a codebase and identify its architectural layers, technology choices, and structure. The subagent produces a machine-parseable architecture document that drives downstream layer-by-layer analysis.

**Output:** `docs/unwind/architecture.md`

## When to Use

- Starting work on an unfamiliar codebase
- Onboarding to a new project
- Before planning a migration or major refactor
- Beginning a security audit or code review

## The Process

### Step 1: Gather Repository Information

**Run these commands FIRST** to get git info for source linking:

```bash
git remote get-url origin 2>/dev/null
git branch --show-current 2>/dev/null
```

Parse the remote URL:
- SSH format: `[email protected]:owner/repo.git` → `https://github.com/owner/repo`
- HTTPS format: `https://github.com/owner/repo.git` → `https://github.com/owner/repo`
- If no remote: use `local` type with null URL

Build the repository info block:
```yaml
repository:
  type: github|gitlab|bitbucket|local
  url: https://github.com/owner/repo  # or null if local
  branch: main                         # or null if local
  link_format: https://github.com/owner/repo/blob/main/{path}#L{start}-L{end}
```

### Step 2: Check for Existing Documentation

Check if `docs/unwind/architecture.md` exists:

```
Glob: docs/unwind/architecture.md
```

- If exists: Pass to subagent as "previous analysis" for refresh mode
- If not: Fresh discovery

### Step 3: Dispatch Discovery Subagent

Dispatch an **Explore** subagent for fast codebase analysis. Note: Explore cannot write files, so you will write the output in Step 4.

**Include the repository info from Step 1 in the prompt:**

```
Task(subagent_type="Explore")
  description: "Discover codebase architecture"
  prompt: |
    [See Subagent Prompt below]

    ## Repository Information (already gathered)
    [paste the repository yaml block from Step 1]
```

The Explore agent should return the complete architecture document content as its output.

### Step 4: Write the Architecture Document

When the Explore subagent completes with the document content:

1. Create the output directory:
   ```bash
   mkdir -p docs/unwind
   ```

2. Write the content to `docs/unwind/architecture.md` using the Write tool

3. Verify the file was created

### Step 5: Present Results and Prompt User

After the subagent completes, present the results to the user:

```
## Architecture Discovery Complete

I've analyzed the codebase and created the architecture document.

**Output:** `docs/unwind/architecture.md`

### Summary
[Include the summary from the subagent - framework, layers detected, etc.]

### Detected Layers
[List layers with their confidence levels]

### Next Steps

Would you like me to:
1. **Continue with layer analysis** - Run `unwind:unwinding-codebase` to dispatch specialist subagents for each layer
2. **Review the architecture document first** - Open `docs/unwind/architecture.md` to verify the detection is accurate

[Use AskUserQuestion to let them choose]
```

**Important:** Always give the user the option to review before proceeding. The architecture document drives all subsequent analysis, so accuracy matters.

---

## Subagent Prompt

Use this prompt when dispatching the discovery subagent:

```
Explore this codebase to identify its architectural layers and structure.

## Your Task

Systematically explore the codebase and return the architecture document content. The main agent will write the file.

**Repository information has already been gathered and will be provided to you.** Use the provided `repository.link_format` for all source links.

## Phase 1: Project Identification

Identify the technology stack by looking for:

**Build System:**
- `package.json` → Node.js/JavaScript
- `pom.xml` / `build.gradle` → Java
- `requirements.txt` / `pyproject.toml` → Python
- `go.mod` → Go
- `Cargo.toml` → Rust
- `*.csproj` → .NET

**Framework:** Check dependencies for Spring Boot, Django, Express, Rails, Next.js, etc.

**Database:** Look for connection strings, ORM config, migration directories.

## Phase 2: Directory Mapping

Scan source directories and map to layers:

| Directory Pattern | Likely Layer |
|-------------------|--------------|
| `repository/`, `dao/`, `data/` | Database |
| `model/`, `entity/`, `domain/` | Domain Model |
| `service/`, `usecase/`, `application/` | Service Layer |
| `controller/`, `api/`, `rest/`, `graphql/` | API Layer |
| `messaging/`, `events/`, `queue/`, `kafka/` | Messaging |
| `components/`, `pages/`, `views/`, `ui/` | Frontend |

## Phase 3: Confidence Assessment

For each layer, assess confidence:
- **High**: Clear directory structure, multiple files, consistent naming
- **Medium**: Some indicators but mixed patterns
- **Low**: Minimal evidence
- **Not Detected**: No evidence found

## Phase 4: Cross-Cutting Concerns

Identify aspects spanning multiple layers:
- Authentication/Authorization
- Logging
- Error Handling
- Caching
- Validation

## Phase 5: Return Architecture Document

**DO NOT attempt to write the file** - you don't have write permissions. Instead, return the complete architecture document content in your response. The main agent will write it to `docs/unwind/architecture.md`.

Return the document in this exact format:

```markdown
# Architecture Discovery: [Project Name]

> **For Claude:** REQUIRED SUB-SKILL: Use unwind:unwinding-codebase to analyze each layer.

## Discovery Metadata

- **Generated:** [ISO timestamp]
- **Project Root:** [path]
- **Framework:** [detected framework]
- **Language:** [primary language]

## Repository Information

```yaml
repository:
  type: github|gitlab|bitbucket|local
  url: https://github.com/owner/repo  # or null if local
  branch: main                         # or null if local
  link_format: https://github.com/owner/repo/blob/main/{path}#L{start}-L{end}
```

**For all downstream agents:** Use `link_format` to create source links. Replace `{path}`, `{start}`, `{end}` with actual values.

## Layer Configuration

```yaml
layers:
  database:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points:
      - path/to/data/layer/
    dependencies: []

  domain_model:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points:
      - path/to/domain/
    dependencies: [database]

  service_layer:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points:
      - path/to/services/
    dependencies: [domain_model]

  api:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points:
      - path/to/controllers/
    dependencies: [service_layer]

  messaging:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points: []
    dependencies: [service_layer]

  frontend:
    status: detected|not_detected
    confidence: high|medium|low
    entry_points: []
    dependencies: [api]

cross_cutting:
  authentication:
    touches: [api, service_layer]
    entry_points:
      - path/to/security/
```

## Database Layer

**Status:** [Detected/Not Detected] | **Confidence:** [High/Medium/Low]

**Entry Points:**
- [directories/files]

**Initial Observations:**
- [What you found - technology, patterns, notable aspects]

---

[Repeat for each layer with status != not_detected]

---

## Cross-Cutting Concerns

### Authentication
**Touches:** [layers]
[Observations]

### [Other concerns...]

---

## Discovery Notes

- [Unknowns, questions, areas needing clarification]
```

{REFRESH_CONTEXT}

## Output

After creating the architecture document, provide a brief summary:
- Project type and framework
- Which layers were detected (with confidence)
- Any notable findings or concerns
```

---

## Refresh Mode Context

If previous architecture.md exists, add this to the subagent prompt:

```
## Previous Analysis

A previous architecture analysis exists. Compare the current codebase state to this previous analysis and:

1. Note any changes in the `## Changes Since Last Discovery` section
2. Update layer status/confidence if changed
3. Add new entry points discovered
4. Remove entry points that no longer exist
5. Update the `last_analyzed` timestamp

Previous analysis:
[CONTENTS OF EXISTING architecture.md]
```

---

## Layer Detection Reference

### Database Layer Indicators
- Directories: `repository/`, `dao/`, `data/`, `persistence/`
- Files: `*Repository.java`, `*_repository.py`, `*.repo.ts`
- ORM: Hibernate, SQLAlchemy, Prisma, TypeORM, Sequelize
- Migrations: Flyway, Liquibase, Alembic, Prisma migrations

### Domain Model Indicators
- Directories: `domain/`, `model/`, `entity/`, `entities/`
- Files: `*Entity.java`, `models.py`, `*.entity.ts`
- Patterns: `@Entity`, `class Model`, aggregates, value objects

### Service Layer Indicators
- Directories: `service/`, `services/`, `usecase/`, `application/`
- Files: `*Service.java`, `*_service.py`, `*.service.ts`
- Patterns: `@Service`, `@Transactional`, business logic methods

### API Layer Indicators
- Directories: `controller/`, `api/`, `rest/`, `routes/`, `graphql/`
- Files: `*Controller.java`, `views.py`, `*.controller.ts`
- Patterns: `@RestController`, `@router`, route definitions

### Messaging Layer Indicators
- Directories: `messaging/`, `events/`, `queue/`, `kafka/`, `rabbitmq/`
- Files: `*Listener.java`, `*Consumer.py`, `*.handler.ts`
- Configs: Kafka, RabbitMQ, SQS configuration

### Frontend Layer Indicators
- Directories: `components/`, `pages/`, `views/`, `ui/`, `src/app/`
- Files: `*.tsx`, `*.vue`, `*.component.ts`
- Configs: React, Vue, Angular, Next.js, Nuxt
start | SkillHub