tegwick
bd74d7d122
Persist INTENT and ecosystem assessments in history/, add ADR-004 for project metrics with Helix Forge correlation, and register WP-0003 and WP-0004 workplans with State Hub. Update SCOPE, README, and agency-framework docs to reflect the two-layer measurement model.
Kaizen Agentic
AI agency framework: 18 specialized agents that arrive in your project informed, learn from experience, and improve over time.
kaizen-agentic provides two things: a library of agent instruction sets you deploy into projects, and an agency framework that gives those agents persistent memory and coordination. Agents accumulate project-scoped knowledge across sessions. A Coach meta-agent synthesises patterns across the entire fleet and briefs incoming agents on what to know first.
This project embraces the Japanese concept of "kaizen" (continuous improvement) applied to AI agent development. Every agent becomes part of an optimization loop where performance is measured, patterns are analyzed, and knowledge is carried forward.
Quick Start
Install the Package
From Source (Development):
git clone https://github.com/kaizen-agentic/kaizen-agentic.git
cd kaizen-agentic
make setup-complete
make agents-install-cli
source .venv/bin/activate # Required for each session
Global Installation (Available from any directory):
git clone https://github.com/kaizen-agentic/kaizen-agentic.git
cd kaizen-agentic
make setup-complete
python3 -m build && make install-global
# No virtual environment activation needed
Local Package Testing:
git clone https://github.com/kaizen-agentic/kaizen-agentic.git
cd kaizen-agentic
make setup-complete
python3 -m build && make install-local
source .venv/bin/activate # Required for each session
From PyPI (Coming Soon):
pip install kaizen-agentic # Available after v1.0.0 publication
# or
pipx install kaizen-agentic # Recommended for global CLI tools
Your First Project (New Users)
👋 New to Kaizen Agentic? Follow our Hello World Tutorial for a complete step-by-step guide.
Create a Project (Experienced Users)
# Create a new project with AI agents
kaizen-agentic init my-project --template python-web
cd my-project
# Set up development environment
make setup-complete
# Start coding with agent assistance!
make help # See all available commands
Add Agents to Existing Project
# Navigate to your project
cd your-existing-project
# Install relevant agents
kaizen-agentic install keepaTodofile keepaChangelog tdd-workflow
# Check what was installed
kaizen-agentic status
Agency Framework
Agents deployed into a project can accumulate project-scoped memory — a structured file written at session close and read at session start. A Coach meta-agent reads across all agent memories and produces targeted orientation briefs for incoming agents.
# Scaffold memory for an agent
kaizen-agentic memory init sys-medic
# Brief an incoming agent using all existing project memories
kaizen-agentic memory brief tdd-workflow
# Review an agent's accumulated knowledge
kaizen-agentic memory show project-management
See docs/agency-framework.md for the full model.
Orientation
Read in this order for strategic context:
- INTENT.md — purpose, boundaries, design principles
- wiki/KaizenAgenticMission.md — product narrative
- wiki/EcosystemIntegration.md — ecosystem composition
- SCOPE.md — repository boundaries and current state
- history/ — persisted assessments and gap analyses
Active workplans: WP-0003 (measurement loop), WP-0004 (ecosystem integration).
Features
- 18 Specialized Agents: Project management, testing, code quality, infrastructure, meta
- Agency Framework: Project-scoped agent memory + Coach meta-agent for cross-agent synthesis
- CLI Tool: Easy agent installation, management, and memory commands (
kaizen-agentic) - Project Templates: Pre-configured setups for different project types
- Claude Code Integration: Seamless integration with Claude Code workflows
- Comprehensive Testing: Full test coverage with multiple testing strategies
Available Agents
Project Management
- keepaTodofile: Manages TODO.md files following Keep a Todofile format
- keepaChangelog: Maintains CHANGELOG.md files following Keep a Changelog format
- keepaContributingfile: Creates and updates CONTRIBUTING.md files
- project-management: General project management and coordination
Development Process
- tdd-workflow: Test-driven development workflow guidance
- requirements-engineering: Requirements analysis and documentation
- test-maintenance: Test suite maintenance and optimization
Code Quality
- code-refactoring: Code improvement and refactoring guidance
- optimization: Agent definition optimization and improvement
- datamodel-optimization: Data model design and optimization
Infrastructure
- setupRepository: Repository initialization and standards compliance
- claude-documentation: Claude Code configuration and documentation
- tooling-optimization: Repository tooling usage optimization
- sys-medic: Infrastructure health monitoring and diagnostics
Meta
- coach: Coaching meta-agent — reads all project agent memories, synthesises cross-agent briefs, and orients incoming agents
Project Templates
# Available templates
kaizen-agentic templates
# python-basic: Basic Python project setup
# python-web: Web application development
# python-cli: Command-line tool development
# python-data: Data science and analysis
# comprehensive: All available agents
Known Issues
Click Library Workaround
The CLI currently implements a workaround for spurious error messages in the Click library. This affects the install command but is transparent to users. See CLICK_WORKAROUND.md for technical details and removal timeline.
User Impact: None - the workaround provides clean CLI output Status: Monitoring Click library updates for resolution