---
id: capability.agents.kaizen-framework
name: Kaizen Agentic Framework
summary: AI agency framework providing 20 deployable agent instruction sets, project memory,
  metrics, role and engagement contracts, and scheduled preparation for governed execution.
owner: kaizen-agentic
status: draft
domain: agents
tags:
- agents
- memory
- coordination
- metrics
- scheduling
- engagements
maturity:
  discovery:
    current: D3
    target: D5
    confidence: medium
    rationale: README, SCOPE, ADRs, and integration contracts document the agent library, memory,
      metrics, scheduling, role and engagement surfaces, and versioned release v1.4.0; CI is present.
  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:
    - 20 specialized agent instruction sets
    - persistent project-scoped agent memory
    - Coach meta-agent for fleet-wide pattern synthesis
    - project metrics and optimizer workflow
    - role packages and file-backed client engagements
    - schedule validation and offline execution-bundle preparation
    broken_expectations: []
    out_of_scope_expectations: []
  reliability:
    level: R0
    confidence: low
    basis: consumer_quality_signals
    known_reliability_risks:
    - downstream execution depends on activity-core, glas-harness, and selected-rein contracts outside this repository
discovery:
  intent: Let agents arrive informed, work within explicit roles and engagement boundaries,
    and improve through project memory, execution evidence, and governed scheduling contracts.
  includes:
  - 20 specialized agent instruction sets
  - persistent memory and coordination framework
  - Coach meta-agent pattern synthesis
  - project execution metrics and optimizer artifacts
  - role packages and forward-deployed engagement lifecycle helpers
  - repo-local schedule manifests and offline preparation bundles
  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 (`kaizen-agentic`)
  - versioned role, engagement, metrics, protocol, and schedule contracts
  target_artifacts: []
  consumption_modes:
  - cli
  - library import
  - file contracts
relations:
  depends_on: []
  supports: []
  related_to: []
evidence:
  documentation:
  - README.md
  tests:
  - tests/
  - .forgejo/workflows/
  consumer_feedback: []
  bug_reports: []
  incidents: []
consumer_guidance:
  recommended_for:
  - projects wanting a deployable, memory-persistent agent fleet with cross-agent coordination
  - governed runtimes needing offline agent orientation and schedule preparation contracts
  not_recommended_for:
  - needs for a single stateless agent (framework overhead not justified)
  known_limitations:
  - this package prepares work but does not schedule, authorize, or invoke an LLM
  - production reliability telemetry is not yet sufficient for a higher reliability rating
promotion_history: []
---

# Kaizen Agentic Framework

## Overview

`kaizen-agentic` is an AI agency framework: 20 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 .forgejo/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`