Solokit - Structured Solo Development with AI and Quality Automation

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Project description

Solokit

https://github.com/user-attachments/assets/b7a5bbaf-6a64-420e-874c-2d12313fd516

Build production software alone with team-level sophistication.

Structured Solo Development with AI and Quality Automation for Claude Code

What is Solokit?

Solokit is a complete development framework for solo developers building production software with AI assistants like Claude Code. It combines minimal scaffolding templates with comprehensive documentation, automated quality gates, intelligent session management, and AI-powered knowledge capture into a cohesive workflow that enables you to build alone with the sophistication of a 10-person engineering team.

The Core Problem

Solo developers using AI assistants face critical challenges:

Setup Time Waste - Spending hours configuring frameworks, linters, tests, CI/CD
Context Loss - AI forgets previous work between sessions
Quality Entropy - Standards slip without enforcement
Knowledge Fragmentation - Learnings and decisions get lost
Lack of Process - No systematic workflow for complex projects

The Solokit Solution

🚀 Start Building in <1 Minute

4 minimal scaffolding templates (T3 Stack, FastAPI, Refine, Next.js)
Comprehensive ARCHITECTURE.md guides with patterns and examples
PRD-driven development workflow
4 quality tiers (Essential → Production-Ready)
All dependencies version-pinned and compatibility-tested
CI/CD, Docker, environment templates included

✨ Perfect Context Continuity

Comprehensive AI briefings restore full project state
Spec-first architecture with complete implementation details
Previous work context for multi-session features
Dependency-aware workflow recommendations

🛡️ Zero-Compromise Quality

Automated gates: tests, linting, formatting, security
Coverage thresholds, mutation testing, E2E tests
Performance monitoring, error tracking (tier 4)
Spec validation before and after sessions

🧠 Knowledge That Grows

AI-powered learning categorization (6 categories)
Automatic extraction from commits and code comments
Smart deduplication and similarity detection
Searchable, filterable knowledge base

Quick Start

1. Install Solokit

# macOS/Linux
pip3 install solokit

# Windows
py -m pip install solokit

First-time macOS users: When you run pip3 for the first time, macOS will prompt you to install Command Line Tools. This is normal and required - the installation takes 5-10 minutes.

2. Initialize Your Project

For new projects:

sk init

For existing projects with code:

sk adopt

Choose from 4 minimal scaffolding stacks (with sk init):

SaaS T3 Stack - Next.js + tRPC + Prisma (full-stack SaaS)
ML/AI FastAPI - FastAPI + Python ML libraries (model serving, data pipelines)
Dashboard Refine - Refine + shadcn/ui (admin panels, internal tools)
Full-Stack Next.js - Next.js + Prisma (general purpose web apps)

Each stack includes comprehensive ARCHITECTURE.md documentation with patterns you'll implement from your PRD.

Select your quality tier:

Essential (60-80% coverage) - Prototypes, MVPs
Standard (80% coverage + security) - Production apps
Comprehensive (90% coverage + E2E + mutation) - Mission-critical
Production-Ready (+ monitoring + observability) - Enterprise-grade

Options: CI/CD workflows, Docker support, environment templates

3. Start Building

# Create your first work item
sk work-new

# Start a development session
sk start

# Claude receives a comprehensive briefing with:
# - Complete work item specification
# - Project documentation and context
# - Technology stack and file structure
# - Related learnings from past sessions
# - Dependency information

# Work with Claude...

# End session with automated quality gates
sk end

That's it! You now have:

✅ Production-ready project setup
✅ Automated quality enforcement
✅ Perfect AI context continuity
✅ Growing knowledge base

💡 Best Used with Claude Code

Solokit is designed to work seamlessly with Claude Code, providing:

Slash Command Interface: Use /start, /end, /work-new, and more without memorizing CLI syntax
Context Continuity: Claude maintains full project context across sessions, understanding your work items, dependencies, and progress
Interactive Workflow: Rich prompts and guided workflows make session management effortless
Quality Automation: Automatic quality gate validation and learning capture integrated into your natural workflow

Quick Start with Claude Code

Initialize your project (one-time setup):
```
sk init
```

Open in Claude Code and use slash commands:

/work-new      # Create your first work item
/start         # Begin a development session with full briefing
/end           # Complete session with quality gates

That's it! Claude Code handles the rest, providing context-aware assistance throughout your development session.

Key Features

🎯 Minimal Scaffolding Templates

Initialize projects with battle-tested configurations and comprehensive documentation:

SaaS T3 Stack (saas_t3)

Next.js 16.0.7, React 19.2.1, tRPC 11.7.1, Prisma 6.19.0
End-to-end type safety patterns documented in ARCHITECTURE.md
Perfect for: SaaS products, B2B apps, complex data models

ML/AI FastAPI (ml_ai_fastapi)

FastAPI 0.121.3, Python 3.11+, SQLModel, Pydantic 2.12.4
Async patterns and service layer architecture documented
Perfect for: ML model serving, data pipelines, Python microservices

Dashboard Refine (dashboard_refine)

Refine 5.0.5, Next.js 16.0.7, shadcn/ui
Data provider and Refine hook patterns documented
Perfect for: Admin panels, internal dashboards, data management

Full-Stack Next.js (fullstack_nextjs)

Next.js 16.0.7, React 19.2.1, Prisma 6.19.0
Server Components and Server Actions patterns documented
Perfect for: Marketing sites, content platforms, e-commerce

All templates include:

Minimal scaffolding (health check endpoint + config only)
Comprehensive ARCHITECTURE.md with code patterns and examples
Exact version pinning (all tested for compatibility)
Framework-specific ESLint/Prettier configurations
Testing setup with framework utilities
TypeScript/Python type checking
Security scanning configured
Docker Compose for local development
CI/CD workflows (GitHub Actions)
Environment variable templates
Three-File Documentation Model (see below)

📚 Documentation-First Development

Every project initialized with sk init includes comprehensive documentation for building from scratch:

Three-File Documentation Model:

File	Purpose	Audience	Generated
README.md	Quick start guide	Human developers	Yes (project-specific)
ARCHITECTURE.md	Technical patterns & examples	Human developers + Claude	No (static template)
CLAUDE.md	AI guidance & Solokit usage	Claude Code	Yes (from template)

Development Guides (in .session/guides/):

Guide	Purpose
STACK_GUIDE.md	Understand your chosen stack's architecture and patterns
PRD_WRITING_GUIDE.md	Write effective PRDs for AI-driven development

CLAUDE.md is a key differentiator - it provides Claude Code with:

Stack-specific architecture rules and patterns
Comprehensive Solokit command usage guide
Work item management instructions
Session workflow documentation
Learning capture best practices
Anti-patterns and common mistakes to avoid

This means Claude Code automatically understands your project's conventions, quality standards, and how to use Solokit effectively from the first session.

ARCHITECTURE.md provides deep technical documentation:

Architecture decisions with rationale and trade-offs
Code patterns and examples specific to your stack
Project structure explanations
Database workflows
Troubleshooting guides

🛡️ Quality Gates

Automated validation prevents technical debt:

Available Checkers:

Tests - Unit, integration, E2E with coverage thresholds
Linting - Code quality (ESLint/Ruff) with auto-fix
Formatting - Code style (Prettier/Ruff) with auto-format
Security - Vulnerability scanning (bandit, safety, npm audit)
Type Checking - Static analysis (TypeScript/mypy)
Documentation - CHANGELOG, README, docstring validation
Spec Completeness - Work item specification validation
Performance - Benchmarks and regression detection

Quality Tiers:

Tier	Use Case	What's Included
Essential	Prototypes, MVPs	Linting, formatting, type-check, basic tests (60-80% coverage)
Standard	Production apps	Essential + Pre-commit hooks, security scanning, dependency auditing
Comprehensive	Mission-critical	Standard + Mutation testing (75%+), E2E tests, integration tests
Production-Ready	Enterprise	Comprehensive + Sentry, OpenTelemetry, performance monitoring, health checks

Configure in .session/config.json:

{
  "quality_gates": {
    "tests": {"enabled": true, "required": true, "coverage_threshold": 80},
    "linting": {"enabled": true, "required": false, "auto_fix": true},
    "security": {"enabled": true, "required": true, "fail_on": "high"}
  }
}

📋 Session Management

Perfect context continuity across all AI interactions:

💡 Recommended: Use Claude Code for the best experience

Start a session in Claude Code:

/start feature_xyz

Claude receives:

Complete Work Item Spec - Full implementation details from .session/specs/feature_xyz.md
Project Documentation - Vision, architecture, PRD
Technology Stack - Auto-detected frameworks and versions
Project Structure - Current file tree
Git Context - Branch status, recent commits
Related Learnings - Past insights relevant to this work
Dependency Context - What this depends on and what depends on it
Milestone Progress - Where this fits in the roadmap
Previous Work Context - For in-progress items: commits made, files changed, quality results

Complete session with automatic quality enforcement:

/end

The /end command asks whether the work item is complete and runs quality gates accordingly:

Complete mode (--complete):

✅ Runs all enabled quality gates (enforced/blocking)
✅ Quality gates must pass to end session
✅ Marks work item as "completed"

Incomplete mode (--incomplete):

✅ Runs quality gates but doesn't block session end (non-blocking)
✅ Useful when running out of context with failing gates
✅ Keeps work item as "in_progress" for later resumption

Both modes automatically:

✅ Updates stack/tree tracking
✅ Extracts learnings from work
✅ Commits with standardized message
✅ Pushes to remote
✅ Generates session summary

Alternative: Terminal Usage (without AI assistance)

sk start feature_xyz  # Start session
sk end                # Complete session

🎯 Work Item Management

Dependency-driven, spec-first workflow:

💡 Recommended: Use Claude Code for interactive work item creation and management

Create and manage work items in Claude Code:

/work-new                              # Create work items interactively
/work-list                             # List all work items
/work-list --status not_started        # Filter by status
/work-list --milestone "v1.0"          # Filter by milestone

/work-next                             # Get smart recommendations (dependencies completed)

/work-graph --critical-path            # Show longest dependency chain
/work-graph --bottlenecks              # Identify blockers
/work-graph --format svg               # Export visual graph

/work-update feature_xyz --status in_progress
/work-update feature_xyz --priority high

Alternative: Terminal Usage (without AI assistance)

sk work-new                        # Create work items interactively
sk work-list                       # List all work items
sk work-list --status not_started
sk work-list --milestone "v1.0"

sk work-next                       # Get recommendations
sk work-graph --critical-path      # Visualize dependencies
sk work-update feature_xyz --status in_progress

Spec-First Architecture:

Work item specifications are the single source of truth:

.session/
├── specs/
│   ├── feature_xyz.md         # Complete implementation guide
│   └── deployment_abc.md
└── tracking/
    └── work_items.json         # Metadata only (status, deps)

6 work item types with structured templates:

Feature - New functionality
Bug - Issue fixes with root cause analysis
Refactor - Code improvements
Security - Security enhancements
Integration Test - Test suites
Deployment - Deployment procedures

Each template includes:

Required sections enforced via validation
Implementation details, acceptance criteria
Testing strategy, validation rules
Type-specific guidelines

🧠 Learning System

AI-powered knowledge capture and curation:

💡 Recommended: Use Claude Code for AI-assisted learning capture

Capture and browse learnings in Claude Code:

/learn                                # Capture learnings during development (AI-assisted)

/learn-show                           # Browse all learnings
/learn-show --category gotchas --tag fastapi

/learn-search "CORS"                  # Search by keyword

/learn-curate                         # Auto-curate (categorize, deduplicate, merge)

Alternative: Terminal Usage (without AI assistance)

sk learn                       # Capture learnings manually
sk learn-show                  # Browse all learnings
sk learn-search "CORS"         # Search by keyword
sk learn-curate                # Run curation

6 Learning Categories (auto-categorized):

Architecture - Design decisions, patterns
Gotchas - Edge cases, pitfalls
Best Practices - Effective approaches
Technical Debt - Areas needing improvement
Performance - Optimization insights
Security - Security discoveries

3 Extraction Sources:

Session summaries ("Learnings Captured" section)
Git commits (LEARNING: annotations)
Code comments (# LEARNING: in changed files)

Smart Deduplication:

Jaccard + containment similarity detection
Automatic merging of similar learnings
Configurable similarity threshold (default: 0.7)

🔄 Adopting Existing Projects

Already have a project? Use sk adopt to add Solokit's session management without modifying your existing code:

sk adopt

What sk adopt does:

Auto-detects your project type (Python, Node.js, TypeScript, Fullstack)
Creates .session/ directory for tracking
Installs Claude Code slash commands
Appends Solokit sections to README.md and CLAUDE.md
Updates .gitignore with Solokit entries
Installs git hooks for quality enforcement

What sk adopt does NOT do:

Modify your existing source code
Overwrite your documentation content
Install project templates or starter code
Change your existing tooling configuration

When to use sk adopt vs sk init:

Scenario	Command
Starting a brand new project	`sk init`
Adding Solokit to existing codebase	`sk adopt`
Project already has package.json/pyproject.toml	`sk adopt`
Want production-ready templates	`sk init`

Example adoption workflow:

# Navigate to your existing project
cd my-existing-project

# Adopt Solokit (interactive prompts)
sk adopt

# Or with arguments
sk adopt --tier=tier-2-standard --coverage=80 --yes

# Start using Solokit
sk work-new
sk start

Commands Reference

💡 Best Experience: Use these commands in Claude Code for AI-assisted development

Session Commands (Claude Code)

/init                 # Initialize new project with template selection
/adopt                # Add Solokit to existing project
/start [item_id]      # Start session with comprehensive briefing
/end                  # Complete session with quality gates
/status               # Quick session overview
/validate             # Pre-flight check (run gates without ending)

Work Item Commands (Claude Code)

/work-new             # Create work item interactively (AI-assisted)
/work-list            # List all work items
/work-show <id>       # Show work item details
/work-update <id>     # Update work item fields
/work-next            # Get next recommended work item
/work-graph           # Visualize dependency graph
/work-delete <id>     # Delete work item (with safety checks)

Learning Commands (Claude Code)

/learn                # Capture learning interactively (AI-assisted)
/learn-show           # Browse all learnings
/learn-search <q>     # Search learnings by keyword
/learn-curate         # Run curation (categorize, deduplicate)

Utility Commands (Claude Code & Terminal)

sk help               # Show all commands with descriptions
sk help <command>     # Show detailed help for specific command
sk version            # Show version information
sk --version, -V      # Show version (global flag)
sk doctor             # Run system diagnostics
sk config show        # Display current configuration
sk config show --json # Display configuration as JSON

Alternative: Terminal Commands (without AI assistance)

Session Commands

sk init               # Initialize new project
sk adopt              # Add Solokit to existing project
sk start [item_id]    # Start session
sk end                # Complete session
sk status             # Session status
sk validate           # Validate readiness

Work Item Commands

sk work-new           # Create work item
sk work-list          # List work items
sk work-show <id>     # Show work item
sk work-update <id>   # Update work item
sk work-next          # Get recommendation
sk work-graph         # Visualize dependencies
sk work-delete <id>   # Delete work item

Learning Commands

sk learn              # Capture learning
sk learn-show         # Browse learnings
sk learn-search <q>   # Search learnings
sk learn-curate       # Run curation

Utility Commands

sk help               # Show all commands
sk help <command>     # Show command help
sk version            # Show version
sk --version, -V      # Show version (flag)
sk doctor             # Run diagnostics
sk config show        # Display config
sk config show --json # Display as JSON

Typical Workflow

graph TD
    Start{New or Existing Project?}
    Start -->|New| A[sk init]
    Start -->|Existing| A2[sk adopt]
    A --> B[Choose Template & Quality Tier]
    A2 --> B2[Choose Quality Tier]
    B --> C[sk work-new]
    B2 --> C
    C --> D[Write Spec]
    D --> E[sk start]
    E --> F[Develop with Claude]
    F --> G{More Changes?}
    G -->|Yes| F
    G -->|No| H[sk validate]
    H --> I{Gates Pass?}
    I -->|No| J[Fix Issues]
    J --> F
    I -->|Yes| K[sk end]
    K --> L{More Work?}
    L -->|Yes| C
    L -->|No| M[Done!]

Installation

Prerequisites

Required:

Python 3.11+ - Core runtime
pip/pip3 - Package installer (see OS-specific notes below)
Git - Version control
Claude Code - Strongly recommended for slash command integration and optimal workflow experience. While Solokit can be used via CLI alone, Claude Code provides the richest experience with interactive prompts, context continuity, and intelligent assistance.

OS-Specific Requirements:

macOS:

Use pip3 instead of pip on fresh installations
Command Line Tools - macOS will prompt you to install these automatically when you first run pip3 (5-10 minute installation, completely normal)
PATH Setup - You may need to add the install location to your PATH (see Troubleshooting below)

Windows:

Use py -m pip instead of pip for reliable installation
Ensure Python is added to PATH during Python installation

Linux:

Use pip3 for Python 3.x installations
May need to install python3-pip package first: sudo apt install python3-pip (Debian/Ubuntu) or sudo dnf install python3-pip (Fedora/RHEL)

Optional Tools (for quality gates):

Testing: pytest (Python), jest (JS/TS)
Linting: ruff (Python), eslint (JS/TS)
Formatting: prettier (JS/TS)
Security: bandit, safety (Python), npm audit (JS)
Visualization: graphviz (dependency graphs)

Quality gates gracefully skip when tools aren't available.

Option 1: PyPI (Recommended)

# macOS/Linux
pip3 install solokit

# Windows
py -m pip install solokit

Post-Installation (macOS):

If you see a warning that sk is not on PATH, add it to your shell configuration:

# For zsh (default on modern macOS)
echo 'export PATH="$HOME/Library/Python/3.11/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc

# For bash
echo 'export PATH="$HOME/Library/Python/3.11/bin:$PATH"' >> ~/.bash_profile
source ~/.bash_profile

Note: Adjust the Python version (3.11) to match your installed version if different.

Option 2: From Source

git clone https://github.com/ankushdixit/solokit.git
cd solokit

# macOS/Linux
pip3 install -e .

# Windows
py -m pip install -e .

Verify Installation

sk status

If sk command is not found, see the Troubleshooting section below.

Troubleshooting

Common Installation Issues

"command not found: sk"

macOS/Linux: The sk command is installed in your Python user bin directory, which may not be on your PATH.

Solution:

# Find where sk is installed
pip3 show solokit

# Add to PATH (example for macOS with zsh)
echo 'export PATH="$HOME/Library/Python/3.11/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc

# Verify
sk status

Windows:

# Add Python Scripts to PATH
# Go to System Properties > Environment Variables
# Add: C:\Users\YourUsername\AppData\Local\Programs\Python\Python311\Scripts

"command not found: pip" (macOS)

Problem: Fresh macOS installations only have pip3, not pip.

Solution: Use pip3 instead:

pip3 install solokit

"xcode-select: note: No developer tools were found"

This is normal on fresh macOS! When you run pip3 for the first time, macOS needs to install Command Line Tools.

Solution:

Click "Install" when prompted
Wait 5-10 minutes for the installation to complete
Then retry: pip3 install solokit

"WARNING: You are using pip version X.X.X"

This warning is safe to ignore. Solokit works with older pip versions. If you want to update pip:

# macOS/Linux
pip3 install --upgrade pip

# Windows
py -m pip install --upgrade pip

Python Version Issues

Problem: Solokit requires Python 3.11 or higher.

Check your Python version:

python3 --version

Solution: If you have an older version, install Python 3.11+ from python.org

Permission Errors on Linux

Problem: Permission denied when installing packages.

Solution: Use --user flag to install in your user directory:

pip3 install --user solokit

Or use a virtual environment (recommended):

python3 -m venv venv
source venv/bin/activate
pip3 install solokit

Getting Help

If you encounter issues not covered here:

Check existing issues: GitHub Issues
Run diagnostics: sk doctor (after installation)
Open a new issue: Include:
- Operating system and version
- Python version (python3 --version)
- Error message (full output)
- Steps to reproduce

Configuration

Configure Solokit via .session/config.json (created during sk init):

{
  "quality_gates": {
    "tests": {
      "enabled": true,
      "required": true,
      "coverage_threshold": 80
    },
    "linting": {
      "enabled": true,
      "required": false,
      "auto_fix": true
    },
    "formatting": {
      "enabled": true,
      "required": false,
      "auto_fix": true
    },
    "security": {
      "enabled": true,
      "required": true,
      "fail_on": "high"
    },
    "documentation": {
      "enabled": true,
      "required": false
    }
  },
  "learning_curation": {
    "auto_curate": true,
    "frequency": 5
  },
  "git": {
    "auto_push": true,
    "auto_merge": false
  }
}

Quality Gate Options:

enabled - Run this gate
required - Block sk end if fails
auto_fix - Automatically fix issues (linting/formatting)
coverage_threshold - Minimum test coverage percentage
fail_on - Security threshold (critical, high, medium, low)

Learning Curation:

auto_curate - Automatically run curation
frequency - Run every N sessions

Git Integration:

auto_push - Automatically push after sk end
auto_merge - Automatically merge branch if work complete

Documentation

Documentation Index - Complete documentation navigation
Architecture Overview - System architecture
Solokit Methodology - Complete framework specification
AI-Augmented Solo Framework - Philosophical context
Learning System Guide - Knowledge capture details
Configuration Guide - Configuration options
Writing Specs - Spec-first best practices
Troubleshooting - Common issues

Project Structure

solokit/
├── .claude/                  # Claude Code integration
│   └── commands/             # 16 slash commands (/sk:init, /sk:start, etc.)
├── src/solokit/              # Python package (standard src/ layout)
│   ├── cli.py                # CLI entry point (sk command)
│   ├── core/                 # Core functionality
│   ├── session/              # Session management
│   ├── work_items/           # Work item CRUD and specs
│   ├── learning/             # Learning capture & curation
│   ├── quality/              # Quality gates
│   ├── visualization/        # Dependency graphs
│   ├── git/                  # Git integration
│   ├── testing/              # Testing utilities
│   ├── deployment/           # Deployment execution
│   ├── project/              # Project initialization
│   └── templates/            # Project templates & work item specs
├── docs/                     # Comprehensive documentation
├── tests/                    # 3,802 tests (100% passing, 97% coverage)
│   ├── unit/                 # Unit tests
│   ├── integration/          # Integration tests
│   └── e2e/                  # End-to-end tests
├── README.md                 # This file
├── CHANGELOG.md              # Version history
├── CONTRIBUTING.md           # Contribution guidelines
└── pyproject.toml            # Package configuration (PEP 517/518)

Why Solokit?

vs. Project Management Tools (Linear, Jira)

✅ AI-native design - Built for Claude Code, not bolted on
✅ Context continuity - Perfect AI briefings, not manual updates
✅ Quality enforcement - Automated gates, not manual reviews
✅ Knowledge capture - AI-powered, not manual documentation

vs. AI Coding Tools (Cursor, Copilot)

✅ Complete framework - Templates + workflow + quality + learning
✅ Production-ready - Not just code completion
✅ Process rigor - Systematic workflow, not ad-hoc
✅ Knowledge accumulation - Learnings persist and grow

vs. Project Templates (Cookiecutter)

✅ Ongoing workflow - Not just initial setup
✅ Minimal scaffolding - Comprehensive docs, not example code
✅ PRD-driven - Build from your requirements, not template assumptions
✅ Quality enforcement - Automated validation throughout
✅ Session management - Perfect context across all work
✅ 4 quality tiers - From MVP to enterprise

vs. Using Claude Code Standalone

While Claude Code is excellent for code generation and exploration, Solokit adds:

✅ Workflow structure - Session-driven development with clear start/end boundaries
✅ Quality enforcement - Automated gates ensure testing, linting, and security standards
✅ Learning capture - Systematic knowledge accumulation across sessions
✅ Work item management - Organize and track progress on multiple features/bugs
✅ Minimal scaffolding - Battle-tested configurations with comprehensive docs
✅ Spec-first architecture - Clear requirements before implementation

Solokit is the only tool that combines:

Minimal scaffolding templates with comprehensive documentation
PRD-driven development workflow
AI-native session management with perfect context
Automated quality enforcement throughout development
AI-powered knowledge capture and curation
Dependency-driven, spec-first workflow

Development Status

Current Version: v0.3.0 (Production-Ready)

Test Coverage: 3,802 tests passing (100%), 97% code coverage

Completed Features

Feature	Status
Core Session Management	✅ Complete
Work Item System	✅ Complete
Dependency Visualization	✅ Complete
Learning Management	✅ Complete
Quality Gates	✅ Complete
Spec-First Architecture	✅ Complete
Minimal Scaffolding Templates (4 stacks)	✅ Complete
Quality Tiers (4 levels)	✅ Complete
Claude Code Integration	✅ Complete

See CHANGELOG.md for detailed release history.

Contributing

Contributions welcome! See CONTRIBUTING.md for guidelines.

# Clone and install
git clone https://github.com/ankushdixit/solokit.git
cd solokit
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Run quality checks
ruff check src/solokit/ tests/
ruff format src/solokit/ tests/
mypy src/solokit

License

MIT License - See LICENSE for details.

Credits

Built for solo developers building production software with AI assistance.

Inspired by professional software development practices adapted for AI-augmented solo development.

Solo doesn't mean shortcuts. Build with team-level sophistication.

🌐 getsolokit.com | 📦 PyPI | 🐙 GitHub

Project details

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This version

0.3.0

Jan 14, 2026

0.2.2

Dec 5, 2025

0.2.1

Dec 4, 2025

0.2.0

Dec 3, 2025

0.1.7

Nov 28, 2025

0.1.6

Nov 27, 2025

0.1.5

Nov 25, 2025

0.1.4

Nov 24, 2025

0.1.3

Nov 15, 2025

0.1.2

Nov 10, 2025

0.1.1

Nov 10, 2025

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solokit 0.3.0

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Solokit

What is Solokit?

The Core Problem

The Solokit Solution

Quick Start

1. Install Solokit

2. Initialize Your Project

3. Start Building

💡 Best Used with Claude Code

Quick Start with Claude Code

Key Features

🎯 Minimal Scaffolding Templates

📚 Documentation-First Development

🛡️ Quality Gates

📋 Session Management

🎯 Work Item Management

🧠 Learning System

🔄 Adopting Existing Projects

Commands Reference

Session Commands (Claude Code)

Work Item Commands (Claude Code)

Learning Commands (Claude Code)

Utility Commands (Claude Code & Terminal)

Session Commands

Work Item Commands

Learning Commands

Utility Commands

Typical Workflow

Installation

Prerequisites

Option 1: PyPI (Recommended)

Option 2: From Source

Verify Installation

Troubleshooting

Common Installation Issues

"command not found: sk"

"command not found: pip" (macOS)

"xcode-select: note: No developer tools were found"

"WARNING: You are using pip version X.X.X"

Python Version Issues

Permission Errors on Linux

Getting Help

Configuration

Documentation

Project Structure

Why Solokit?

vs. Project Management Tools (Linear, Jira)

vs. AI Coding Tools (Cursor, Copilot)

vs. Project Templates (Cookiecutter)

vs. Using Claude Code Standalone

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