starter-workflows/agentic/weekly-repo-map.md

---
description: Generates a weekly ASCII tree map visualization of repository file structure and size distribution

on:
  schedule: weekly on monday around 15:00
  workflow_dispatch:

permissions:
  contents: read
  issues: read
  pull-requests: read

tools:
  edit:
  bash:
    - "*"

safe-outputs:
  create-issue:
    expires: 7d
    title-prefix: "[repo-map] "
    labels: [documentation]
    max: 1
    close-older-issues: true
  noop:

timeout-minutes: 10
---

# Repository Tree Map Generator

Generate a comprehensive ASCII tree map visualization of the repository file structure.

## Mission

Your task is to analyze the repository structure and create an ASCII tree map that visualizes:
1. Directory hierarchy
2. File sizes (relative visualization)
3. File counts per directory
4. Key statistics about the repository

## Analysis Steps

### 1. Collect Repository Statistics

Use bash tools to gather:
- **Total file count** across the repository
- **Total repository size** (excluding .git directory)
- **File type distribution** (count by extension)
- **Largest files** in the repository (top 10)
- **Largest directories** by total size
- **Directory depth** and structure

Example commands you might use:
```bash
# Count total files
find . -type f -not -path "./.git/*" | wc -l

# Get repository size
du -sh . --exclude=.git

# Count files by extension
find . -type f -not -path "./.git/*" | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20

# Find largest files
find . -type f -not -path "./.git/*" -exec du -h {} + | sort -rh | head -10

# Directory sizes
du -h --max-depth=2 --exclude=.git . | sort -rh | head -15
```

### 2. Generate ASCII Tree Map

Create an ASCII visualization that shows:
- **Directory tree structure** with indentation
- **Size indicators** using symbols or bars (e.g., █ ▓ ▒ ░)
- **File counts** in brackets [count]
- **Relative size representation** (larger files/directories shown with more bars)

Example visualization format:
```
Repository Tree Map
===================

/ [1234 files, 45.2 MB]
│
├─ src/ [456 files, 28.5 MB] ██████████████████░░
│  ├─ core/ [78 files, 5.2 MB] ████░░
│  ├─ utils/ [34 files, 3.1 MB] ███░░
│  └─ tests/ [124 files, 12.8 MB] ████████░░
│
├─ docs/ [234 files, 8.7 MB] ██████░░
│  └─ content/ [189 files, 7.2 MB] █████░░
│
├─ .github/ [45 files, 2.1 MB] ██░░
│  └─ workflows/ [32 files, 1.4 MB] █░░
│
└─ tests/ [78 files, 3.5 MB] ███░░
```

### Visualization Guidelines

- Use **box-drawing characters** for tree structure: │ ├ └ ─
- Use **block characters** for size bars: █ ▓ ▒ ░
- Scale the visualization bars **proportionally** to sizes
- Keep the tree **readable** - don't go too deep (max 3-4 levels recommended)
- Add **type indicators** using emojis:
  - 📁 for directories
  - 📄 for files
  - 🔧 for config files
  - 📚 for documentation
  - 🧪 for test files

### 3. Generate Key Statistics

Compute and include:
- **Total repository size** (excluding .git)
- **Total file count** by type (source, tests, docs, config, etc.)
- **Largest files** (top 10 by size)
- **Most file-dense directories** (top 5 by file count)
- **File type breakdown** (e.g., .ts, .js, .py, .go, etc.)

### 4. Output Format

Create a GitHub issue with the complete tree map and statistics. Use proper markdown formatting with code blocks for the ASCII art.

Structure the issue body as follows:

```markdown
### Repository Overview

Brief 1-2 sentence summary of the repository structure and size.

### File Structure

\`\`\`
[Your ASCII tree map here]
\`\`\`

### Key Statistics

#### By File Type
[Table or list of file counts by extension]

#### Largest Files
[Top 10 largest files with sizes]

#### Directory Sizes
[Top directories by total size]
```

## Important Notes

- **Exclude .git directory** from all calculations to avoid skewing results
- **Exclude package manager directories** (node_modules, vendor, etc.) if present
- **Handle special characters** in filenames properly
- **Format sizes** in human-readable units (KB, MB, GB)
- **Round percentages** to 1-2 decimal places
- **Sort intelligently** - largest first for most sections
- **Be creative** with the ASCII visualization but keep it readable
- **Test your bash commands** before including them in analysis
- The tree map should give a **quick visual understanding** of the repository structure and size distribution

## Security

Treat all repository content as trusted since you're analyzing the repository you're running in. However:
- Don't execute any code files
- Don't read sensitive files (.env, secrets, etc.)
- Focus on file metadata (sizes, counts, names) rather than content

## Tips

Your terminal is already in the workspace root. No need to use `cd`.

**Important**: If no action is needed after completing your analysis, you **MUST** call the `noop` safe-output tool with a brief explanation. Failing to call any safe-output tool is the most common cause of safe-output workflow failures.

```json
{"noop": {"message": "No action needed: [brief explanation of what was analyzed and why]"}}
```