sizely

A command-line tool that performs T-shirt size estimation, calculates sprint capacity, and finds the optimal combination of tasks for the target sprint point.

🎯 Features

• Calculate Sprint Points: Convert T-shirt size estimates (XS, S, M, L) to points
• Point Breakdown: Find all possible task combinations for target points
• JSON Support: Accept input from files or command-line JSON strings
• Multiple Output Formats: Human-readable tables and JSON for automation

📦 Installation

Using Go Install

go install github.com/gr1m0h/sizely/cmd/sizely@latest

Building from Source

git clone https://github.com/gr1m0h/sizely.git
cd sizely
make build

🚀 Quick Start

Calculate Points from Tasks

# From JSON file (estimate is default command)
sizely points --file examples/basic/tasks.json

# From JSON string
sizely points --data '{"xs":3,"s":2,"m":1,"l":1}'

Find Task Combinations

# Find all combinations for 33 points
sizely tasks 33

# Limit to maximum 10 tasks
sizely tasks 33 --count 10

📊 T-shirt Size Points

Size	Points	Time Estimate
XS	1	30min - 4hrs
S	3	4hrs - 1 day
M	5	2-3 days
L	10	1 week

📋 Usage Examples

Basic Calculation

$ sizely points --data '{"xs":3,"s":2,"m":1,"l":1}'

📊 Sprint Capacity Calculation
═══════════════════════════════
XS (1pt):   3 tasks =  3 points
S  (3pt):   2 tasks =  6 points
M  (5pt):   1 tasks =  5 points
L (10pt):   1 tasks = 10 points
───────────────────────────────
Total:      7 tasks = 24 points

Reverse Calculation

$ sizely tasks 33

🔍 Finding combinations for 33 points (max 15 tasks)
═══════════════════════════════════════════════════
Found 12 combination(s):

 1. L×3 + XS×3 = 33 points (6 tasks)
    ✅ Good mix of large and small tasks

 2. L×2 + M×2 + XS×3 = 33 points (7 tasks)
    ✅ Good mix of large and small tasks

🔧 JSON Input Format

{
  "xs": 2,
  "s": 3,
  "m": 1,
  "l": 2
}

Development Setup

# Clone the repository
git clone https://github.com/gr1m0h/sizely.git
cd sizely

# Install dependencies
go mod download

# Run tests
make test

# Build
make build

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.