134 lines
4.7 KiB
Markdown
134 lines
4.7 KiB
Markdown
---
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id: capability.agents.kaizen-framework
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name: Kaizen Agentic Framework
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summary: AI agency framework providing 20 deployable agent instruction sets, project memory,
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metrics, role and engagement contracts, and scheduled preparation for governed execution.
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owner: kaizen-agentic
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status: draft
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domain: agents
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tags:
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- agents
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- memory
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- coordination
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- metrics
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- scheduling
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- engagements
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maturity:
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discovery:
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current: D3
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target: D5
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confidence: medium
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rationale: README, SCOPE, ADRs, and integration contracts document the agent library, memory,
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metrics, scheduling, role and engagement surfaces, and versioned release v1.4.0; CI is present.
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availability:
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current: A2
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target: A3
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confidence: medium
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rationale: Installable via `git clone` + `make setup-complete` + `make agents-install-cli`, with both
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source and global installation paths documented; pyproject-packaged.
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external_evidence:
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completeness:
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level: C1
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confidence: low
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basis: scope_vs_intent_and_consumer_expectations
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satisfied_expectations:
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- 20 specialized agent instruction sets
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- persistent project-scoped agent memory
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- Coach meta-agent for fleet-wide pattern synthesis
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- project metrics and optimizer workflow
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- role packages and file-backed client engagements
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- schedule validation and offline execution-bundle preparation
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broken_expectations: []
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out_of_scope_expectations: []
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reliability:
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level: R0
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confidence: low
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basis: consumer_quality_signals
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known_reliability_risks:
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- downstream execution depends on activity-core, glas-harness, and selected-rein contracts outside this repository
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discovery:
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intent: Let agents arrive informed, work within explicit roles and engagement boundaries,
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and improve through project memory, execution evidence, and governed scheduling contracts.
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includes:
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- 20 specialized agent instruction sets
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- persistent memory and coordination framework
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- Coach meta-agent pattern synthesis
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- project execution metrics and optimizer artifacts
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- role packages and forward-deployed engagement lifecycle helpers
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- repo-local schedule manifests and offline preparation bundles
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excludes:
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- the underlying LLM inference itself (agents are instruction sets, not a model)
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assumptions: []
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use_cases: []
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research_memos: []
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availability:
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current_level: A2
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target_level: A3
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current_artifacts:
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- Python package (`kaizen-agentic`) v1.4.0
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- CLI (`kaizen-agentic`)
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- versioned role, engagement, metrics, protocol, and schedule contracts
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target_artifacts: []
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consumption_modes:
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- cli
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- library import
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- file contracts
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relations:
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depends_on: []
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supports: []
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related_to: []
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evidence:
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documentation:
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- README.md
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tests:
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- tests/
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- .forgejo/workflows/
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consumer_feedback: []
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bug_reports: []
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incidents: []
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consumer_guidance:
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recommended_for:
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- projects wanting a deployable, memory-persistent agent fleet with cross-agent coordination
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- governed runtimes needing offline agent orientation and schedule preparation contracts
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not_recommended_for:
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- needs for a single stateless agent (framework overhead not justified)
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known_limitations:
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- this package prepares work but does not schedule, authorize, or invoke an LLM
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- production reliability telemetry is not yet sufficient for a higher reliability rating
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promotion_history: []
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---
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# Kaizen Agentic Framework
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## Overview
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`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.
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## Assessment notes
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### Discovery
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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.
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### Availability
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Installable via `git clone` + `make setup-complete` + `make agents-install-cli`, with both source and global installation paths documented; pyproject-packaged.
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### Completeness
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First-pass honest assessment from the REUSE-WP-0017 coverage campaign
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(reuse-surface). No external consumer feedback exists yet; levels reflect
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scope-vs-intent documentation quality, not internal code quality.
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### Reliability
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No production consumer telemetry exists yet; reliability level is
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intentionally conservative pending REUSE-WP-0019 reuse-telemetry evidence.
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## Promotion checklist
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- [x] ID follows `capability.<domain>.<name>` pattern
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- [x] Maturity enums match `specs/CapabilityMaturityStandard.md`
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- [x] `external_evidence` is populated separately from `maturity`
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- [ ] Relations reference valid capability IDs (none yet)
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- [x] Index entry added in `registry/indexes/capabilities.yaml`
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