Files

tegwick 3acd5c1064 feat(agents): add scope-analyst agent + fix project-management category

- Add agent-scope-analyst.md: repo scope analysis persona with embedded SCOPE.md template
- Fix agent-project-management.md: add missing category field (was causing ValueError in AgentRegistry)
- Add scope-analyst row to architecture.md category table (project-management category)
- Add SCOPE.md for kaizen-agentic itself

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-03-17 23:10:12 +01:00

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SCOPE

This file helps you quickly understand what this repository is about, when it is relevant, and when it is not. It is intentionally lightweight and may be incomplete.

One-liner

AI agent development framework providing specialized agent personas (markdown instruction sets) and CLI scaffolding tools for embedding domain expertise into Claude Code sessions.

Core Idea

Kaizen-agentic makes recurring development workflows (TDD, refactoring, project management, documentation) first-class by packaging them as named agent personas. You invoke an agent by name, load its instruction set, and follow it — the agent defines the workflow, Claude Code executes it. The "kaizen" (continuous improvement) philosophy means agents are refined based on performance over time.

In Scope

17+ agent definition files (agents/agent-*.md) — markdown persona instruction sets
Agent categories: testing, quality, process, infrastructure, release, documentation
CLI tooling: kaizen-agentic init/install/status for project scaffolding
Project templates (python-basic, python-web, python-cli, python-data, comprehensive)
Python framework: Agent base class, AgentConfig dataclass, OptimizationLoop for performance tracking
Custodian MCP integration: list_kaizen_agents() and get_kaizen_agent() tools

Out of Scope

Agent runtime / execution engine (agents are persona definitions; execution is Claude Code's responsibility)
LLM orchestration or multi-agent debate systems
Project-specific implementation (agents guide; they do not build the software)
Commercial features or PyPI distribution (pre-v1.0)

Relevant When

Starting a guided development workflow (TDD, refactoring, testing, requirements)
Scaffolding a new project with consistent structure and best-practice tooling
Looking up what specialized agent personas are available for a domain session
Contributing a new agent persona to the ecosystem

Not Relevant When

Ad-hoc, one-off scripting with no need for structured guidance
Non-Claude-Code development environments
Need for runtime orchestration or scheduling (not a scheduler)

Current State

Status: experimental → stabilizing (v1.0.2 released)
Implementation: ~85% — 17 agents defined, CLI functional, templates working; optimization loop pattern established but not exercised at scale
Stability: stable CLI and agent loading
Usage: installed in dev projects; agents callable via Custodian MCP hub-wide

How It Fits

Upstream dependencies: Claude Code (agent invocation), kaizen philosophy
Downstream consumers: Custodian State Hub (loads agents via MCP); all six domains (teams use agents for guided workflows)
Often used with: the-custodian (MCP integration), markitect_project (project-management agent), activity-core (scaffolding)

Terminology

Preferred terms: agent, agent persona, AgentConfig, project template
Also known as: "kaizen agents", "the agent library"
Potentially confusing terms: "Agent" here is a persona/instruction set, not a running process

the-custodian — hosts MCP tools that load agents; custodian agent copies live in the-custodian/agents/
markitect_project — references kaizen-agentic as a capability submodule

Getting Oriented

Start with: README.md (quick start, agent list, installation)
Key files / directories: agents/ (all persona definitions), src/kaizen_agentic/ (Python framework), templates/ (project scaffolds)
Entry points: kaizen-agentic --help; or via MCP: get_kaizen_agent("scope-analyst")

3.6 KiB Raw Blame History