---
id: capability.agents.kaizen-framework
name: Kaizen Agentic Framework
summary: AI agency framework providing 18 specialized deployable agent instruction sets plus persistent,
  project-scoped memory and cross-agent coordination via a Coach meta-agent.
owner: kaizen-agentic
status: draft
domain: agents
tags:
- agents
- memory
- coordination
maturity:
  discovery:
    current: D3
    target: D5
    confidence: medium
    rationale: README documents the agent library, the agency framework (persistent memory, Coach meta-agent
      synthesising fleet-wide patterns), and a versioned release (v1.4.0); has .gitea/workflows CI.
  availability:
    current: A2
    target: A3
    confidence: medium
    rationale: Installable via `git clone` + `make setup-complete` + `make agents-install-cli`, with both
      source and global installation paths documented; pyproject-packaged.
external_evidence:
  completeness:
    level: C1
    confidence: low
    basis: scope_vs_intent_and_consumer_expectations
    satisfied_expectations:
    - 18 specialized agent instruction sets
    - persistent project-scoped agent memory
    - Coach meta-agent for fleet-wide pattern synthesis
    broken_expectations: []
    out_of_scope_expectations: []
  reliability:
    level: R0
    confidence: low
    basis: consumer_quality_signals
    known_reliability_risks:
    - no external reuse evidence yet outside the originating project
discovery:
  intent: Let agents arrive in a project already informed and improve over time through persistent, project-scoped
    memory and fleet-wide coordination via a Coach meta-agent.
  includes:
  - 18 specialized agent instruction sets
  - persistent memory and coordination framework
  - Coach meta-agent pattern synthesis
  excludes:
  - the underlying LLM inference itself (agents are instruction sets, not a model)
  assumptions: []
  use_cases: []
  research_memos: []
availability:
  current_level: A2
  target_level: A3
  current_artifacts:
  - Python package (`kaizen-agentic`) v1.4.0
  - CLI (`agents-install-cli`)
  target_artifacts: []
  consumption_modes:
  - cli
  - library import
relations:
  depends_on: []
  supports: []
  related_to: []
evidence:
  documentation:
  - README.md
  tests:
  - tests/
  - .gitea/workflows/
  consumer_feedback: []
  bug_reports: []
  incidents: []
consumer_guidance:
  recommended_for:
  - projects wanting a deployable, memory-persistent agent fleet with cross-agent coordination
  not_recommended_for:
  - needs for a single stateless agent (framework overhead not justified)
  known_limitations:
  - no cross-project reuse evidence recorded yet
promotion_history: []
---

# Kaizen Agentic Framework

## Overview

`kaizen-agentic` is an AI agency framework: 18 specialized agents deployable into any project, each gaining persistent project-scoped memory and coordination through a Coach meta-agent that synthesises fleet-wide patterns and briefs incoming agents.

## Assessment notes

### Discovery

README documents the agent library, the agency framework (persistent memory, Coach meta-agent synthesising fleet-wide patterns), and a versioned release (v1.4.0); has .gitea/workflows CI.

### Availability

Installable via `git clone` + `make setup-complete` + `make agents-install-cli`, with both source and global installation paths documented; pyproject-packaged.

### Completeness

First-pass honest assessment from the REUSE-WP-0017 coverage campaign
(reuse-surface). No external consumer feedback exists yet; levels reflect
scope-vs-intent documentation quality, not internal code quality.

### Reliability

No production consumer telemetry exists yet; reliability level is
intentionally conservative pending REUSE-WP-0019 reuse-telemetry evidence.

## Promotion checklist

- [x] ID follows `capability.<domain>.<name>` pattern
- [x] Maturity enums match `specs/CapabilityMaturityStandard.md`
- [x] `external_evidence` is populated separately from `maturity`
- [ ] Relations reference valid capability IDs (none yet)
- [x] Index entry added in `registry/indexes/capabilities.yaml`