Hi — wanted to make you aware that KubeStellar Console now includes an AI-Codebase Maturity Model (ACMM) dashboard that scores any public GitHub repo against a 5-level framework for AI-assisted engineering — and the Agentic Engineering Framework is one of the four source frameworks it detects criteria from.
→ Run your repo through it
What the ACMM dashboard does
The dashboard scans a repo's file structure, workflows, and config for 40+ criteria drawn from four frameworks:
- ACMM (the 5-level model itself) — our paper at https://arxiv.org/abs/2604.09388
- Fullsend (fullsend-ai) — readiness + autonomy criteria
- Agentic Engineering Framework (your project) — governance criteria
- Claude Reflect (BayramAnnakov) — self-tuning criteria
Each criterion has a detection pattern (file path, workflow name, regex). The dashboard computes a maturity level L1–L5:
| Level |
Role |
Characteristic |
| L1 Assisted |
Executor |
AI suggests completions, no persistent instructions |
| L2 Instructed |
Rule-writer |
Judgment encoded in CLAUDE.md / AGENTS.md / Copilot instructions |
| L3 Measured |
Analyst |
Metrics instrument the AI loop itself |
| L4 Adaptive |
Governor |
Metrics feed back into instructions + gating thresholds |
| L5 Self-Sustaining |
Strategist |
Codebase proposes/triages/gates its own work |
AEF-specific criteria the dashboard detects:
- Task traceability ledger — `.agent/tasks/`, `docs/agent-tasks/`, `agent-tasks.md`
- Structural gates — `CODEOWNERS`, `.agent/boundaries.yml`
- Session continuity doc — CLAUDE.md / AGENTS.md / .cursorrules / copilot-instructions
- Audit trail — `.github/workflows/ai-audit.yml`
- Cross-tool agent config — AGENTS.md / docs/ai-contributors.md
- Change classification policy — `docs/change-classification.md` / `.github/change-tiers.yml`
Why we're reaching out
AEF's governance patterns are the load-bearing signals for the L2–L4 transitions in the ACMM — we treat "code can lie, config cannot" as a core invariant. We wanted you to know your framework is credited as a source and linked from every dashboard scan that detects one of these criteria.
Open source — criteria definitions at:
PRs to refine detection patterns are welcome — if AEF defines a signal we're not detecting, we'd like to add it. Feel free to close if not relevant.
Hi — wanted to make you aware that KubeStellar Console now includes an AI-Codebase Maturity Model (ACMM) dashboard that scores any public GitHub repo against a 5-level framework for AI-assisted engineering — and the Agentic Engineering Framework is one of the four source frameworks it detects criteria from.
→ Run your repo through it
What the ACMM dashboard does
The dashboard scans a repo's file structure, workflows, and config for 40+ criteria drawn from four frameworks:
Each criterion has a detection pattern (file path, workflow name, regex). The dashboard computes a maturity level L1–L5:
AEF-specific criteria the dashboard detects:
Why we're reaching out
AEF's governance patterns are the load-bearing signals for the L2–L4 transitions in the ACMM — we treat "code can lie, config cannot" as a core invariant. We wanted you to know your framework is credited as a source and linked from every dashboard scan that detects one of these criteria.
Open source — criteria definitions at:
PRs to refine detection patterns are welcome — if AEF defines a signal we're not detecting, we'd like to add it. Feel free to close if not relevant.