tegwick
3acd5c1064
- 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>
95 lines
3.6 KiB
Markdown
95 lines
3.6 KiB
Markdown
# SCOPE
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> This file helps you quickly understand what this repository is about,
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> when it is relevant, and when it is not.
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> It is intentionally lightweight and may be incomplete.
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---
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## One-liner
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AI agent development framework providing specialized agent personas (markdown instruction sets) and CLI scaffolding tools for embedding domain expertise into Claude Code sessions.
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---
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## Core Idea
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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.
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---
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## In Scope
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- 17+ agent definition files (`agents/agent-*.md`) — markdown persona instruction sets
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- Agent categories: testing, quality, process, infrastructure, release, documentation
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- CLI tooling: `kaizen-agentic init/install/status` for project scaffolding
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- Project templates (python-basic, python-web, python-cli, python-data, comprehensive)
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- Python framework: `Agent` base class, `AgentConfig` dataclass, `OptimizationLoop` for performance tracking
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- Custodian MCP integration: `list_kaizen_agents()` and `get_kaizen_agent()` tools
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---
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## Out of Scope
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- Agent runtime / execution engine (agents are persona definitions; execution is Claude Code's responsibility)
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- LLM orchestration or multi-agent debate systems
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- Project-specific implementation (agents guide; they do not build the software)
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- Commercial features or PyPI distribution (pre-v1.0)
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---
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## Relevant When
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- Starting a guided development workflow (TDD, refactoring, testing, requirements)
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- Scaffolding a new project with consistent structure and best-practice tooling
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- Looking up what specialized agent personas are available for a domain session
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- Contributing a new agent persona to the ecosystem
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---
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## Not Relevant When
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- Ad-hoc, one-off scripting with no need for structured guidance
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- Non-Claude-Code development environments
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- Need for runtime orchestration or scheduling (not a scheduler)
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---
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## Current State
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- Status: experimental → stabilizing (v1.0.2 released)
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- Implementation: ~85% — 17 agents defined, CLI functional, templates working; optimization loop pattern established but not exercised at scale
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- Stability: stable CLI and agent loading
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- Usage: installed in dev projects; agents callable via Custodian MCP hub-wide
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---
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## How It Fits
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- Upstream dependencies: Claude Code (agent invocation), kaizen philosophy
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- Downstream consumers: Custodian State Hub (loads agents via MCP); all six domains (teams use agents for guided workflows)
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- Often used with: the-custodian (MCP integration), markitect_project (project-management agent), activity-core (scaffolding)
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---
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## Terminology
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- Preferred terms: agent, agent persona, AgentConfig, project template
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- Also known as: "kaizen agents", "the agent library"
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- Potentially confusing terms: "Agent" here is a persona/instruction set, not a running process
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---
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## Related / Overlapping Repositories
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- `the-custodian` — hosts MCP tools that load agents; custodian agent copies live in `the-custodian/agents/`
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- `markitect_project` — references kaizen-agentic as a capability submodule
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---
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## Getting Oriented
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- Start with: `README.md` (quick start, agent list, installation)
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- Key files / directories: `agents/` (all persona definitions), `src/kaizen_agentic/` (Python framework), `templates/` (project scaffolds)
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- Entry points: `kaizen-agentic --help`; or via MCP: `get_kaizen_agent("scope-analyst")`
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