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.
1.5 KiB
1.5 KiB
Architecture
kaizen-agentic has two distinct layers:
1. Python framework (src/kaizen_agentic/)
core.py—Agent(abstract base) +AgentConfig(dataclass). Tracks performance, supports config updates, implements kaizen interface.optimization.py—OptimizationLoop(runs improvement cycles, detects trends, generates recommendations) +PerformanceMetrics(execution time, success rate, quality scores).metrics.py—MetricsStore+OptimizerStore(project-scoped.kaizen/metrics/per ADR-004).
2. Agent definitions (agents/ — 20 files)
Markdown instruction sets read and followed by Claude. Not executables. Naming convention: agent-{name}.md.
Packaged copies live in src/kaizen_agentic/data/agents/ for pip install distribution.
| Category | Agents |
|---|---|
| Testing | tdd-workflow, test-maintenance, testing-efficiency |
| Quality | code-refactoring, datamodel-optimization |
| Process | requirements-engineering, keepaTodofile, keepaChangelog, keepaContributingfile, project-management, priority-evaluation, scope-analyst |
| Infrastructure | setupRepository, tooling-optimization, sys-medic |
| Release | releaseManager |
| Docs | claude-documentation |
| Support | wisdom-encouragement |
| Meta | coach, optimization |
Custodian integration
The state-hub MCP resolves the agents directory via host_paths[hostname] → local_path. Tools: list_kaizen_agents(category?), get_kaizen_agent(name).