Add make package-check/publish-gitea, tag-triggered Gitea Actions workflow,
PACKAGE_RELEASE.md, and update README/GETTING_STARTED install instructions
for the Coulomb registry (v1.1.0+).
Add kaizen-agentic feedback CLI, Gitea issue templates, CI workflow,
pre-commit hooks, FEEDBACK/TELEMETRY docs, and cross-platform path tests.
Improve CLI registry error messages; remove agents_backup scaffolding.
Apply black formatting across src/tests for CI consistency.
State Hub message sent to agentic-resources for Helix correlation doc link.
Sync coach, sys-medic, scope-analyst, optimization, and updated
tdd-workflow to packaged data (20 agents). Update architecture.md,
README orientation, and CHANGELOG for the metrics loop. Mark WP-0003
completed.
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.
- Add make install-global target with intelligent installation methods
- Support pipx (recommended), pip --user, and fallback options
- Resolve issue where kaizen-agentic was only available in local venv
- Update documentation to clearly explain 4 installation options:
- Development mode (local venv)
- Global installation (any directory)
- Local package testing (local venv)
- Future PyPI installation
- CLI now available globally from any directory after make install-global
Fixes the core issue where users couldn't access kaizen-agentic from other repos.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add Option B: From Local Package installation instructions
- Include make install-local target in both README.md and GETTING_STARTED.md
- Provide clear path for testing PyPI-equivalent installation locally
- Maintains development, local package, and future PyPI installation options
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add agent-releaseManager.md with comprehensive publication workflow guidance
- Add 6 release- prefixed make targets for structured release process:
- release-check: Validate release readiness
- release-prepare: Build packages and prepare release
- release-test: Test publication via TestPyPI
- release-publish: Publish to production PyPI
- release-finalize: Post-release tasks (tags, GitHub releases)
- release-rollback: Emergency rollback procedures
- Update pyproject.toml version from 0.1.0 to 1.0.0 for consistency with CHANGELOG.md
- Update installation documentation in README.md and GETTING_STARTED.md
- Add current "from source" installation instructions
- Maintain "from PyPI" instructions for post-publication
- Framework now ready for v1.0.0 publication with complete release workflow
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Major documentation improvements:
- Fixed all outdated agent names throughout README.md and GETTING_STARTED.md
- Updated agent references from old names (todo-keeper, changelog-keeper, setup-repository)
to new names (keepaTodofile, keepaChangelog, setupRepository)
- Created comprehensive HELLO_WORLD_TUTORIAL.md with step-by-step guide for new users
- Added prominent tutorial links in README.md and GETTING_STARTED.md for better discoverability
- Updated Python version requirements from 3.8 to 3.9 in project templates
- Enhanced first-time user experience with clear guidance and working examples
Documentation now provides:
✅ Working commands that match actual agent names
✅ Clear separation between new users and experienced users
✅ Complete tutorial from installation to running code
✅ Proper guidance for scenario one (greenfield projects)
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Complete implementation of the agent distribution framework including:
CORE INFRASTRUCTURE:
- AgentRegistry: Agent discovery, categorization, and dependency management
- AgentInstaller: Agent installation, updates, and removal with safety measures
- ProjectInitializer: Template-based project initialization with agent integration
- CLI Tool: Comprehensive kaizen-agentic command-line interface
DISTRIBUTION FEATURES:
- Python package distribution with console script entry point
- Agent categorization (project-management, development-process, code-quality, etc.)
- Project templates (python-basic, python-web, python-cli, python-data, comprehensive)
- Dependency resolution and validation
- Idempotent operations with backup and rollback support
CLI COMMANDS:
- kaizen-agentic init: Initialize new projects with agents
- kaizen-agentic install/update/remove: Manage agents in existing projects
- kaizen-agentic list/status/validate: Discovery and maintenance
- kaizen-agentic templates: Project template management
INTEGRATION & DOCUMENTATION:
- Makefile targets for agent management (list-agents, update-agents, etc.)
- Automatic Claude Code configuration updates (CLAUDE.md)
- Comprehensive documentation (GETTING_STARTED, AGENT_DISTRIBUTION, CLI_CHEAT_SHEET)
- Multi-language build system integration examples
- Complete test coverage for all components
PACKAGE STRUCTURE:
- Console script: kaizen-agentic command available globally
- Package data: All agents included for distribution
- Dependencies: click, pyyaml for CLI and parsing
- Testing: Comprehensive test suite for registry and installer
This enables sharing specialized AI agents across projects with easy installation,
updates, and management through both CLI and integrated Makefile targets.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
