The problem
Most AI-assisted coding today is "vibe coding" — you prompt, the AI writes, you accept. No review. No independent evaluation. No captured reasoning.
The code works (maybe), but nobody understands why it was built that way.
What I built
An open-source framework template for Claude Code that enforces a disciplined development loop:
Plan → Build → Review → Learn → Ship
11 Specialist Agents
| Agent | What It Does |
|---|---|
| Architecture Consultant | Structural alignment, component boundaries |
| Security Specialist | Vulnerabilities, auth patterns, threat modeling |
| QA Specialist | Test coverage, edge cases, reliability |
| Performance Analyst | Latency, scalability, resource efficiency |
| UX Evaluator | Interaction flow, accessibility, platform conventions |
| Independent Perspective | Anti-groupthink, hidden assumptions, unconsidered alternatives |
| + 5 more | Docs, education, project analysis, lineage tracking, facilitation |
16 Slash Commands
-
/plan→ Spec-driven feature planning -
/build_module→ Build with mid-build checkpoint reviews -
/review→ Multi-agent specialist code review -
/deliberate→ Structured multi-agent discussion -
/ship→ Full release workflow with quality gates -
/walkthrough→ Guided code explanation -
/quiz→ Comprehension assessment - ...and 9 more for discovery, analysis, retrospectives, and knowledge management.
The Principle I Care Most About
The agent that writes code is never the sole reviewer.
Every change gets independent evaluation from specialists who didn't participate in generation. This single rule prevents the "AI echo chamber" where the same model approves its own work.
Education Gates
Code doesn't merge until you understand it:
Walkthrough → Quiz → Explain-back → Merge
The AI doesn't just build for you — it teaches you what it built and why.
Four-Layer Capture Stack
Every decision, trade-off, and discussion is recorded:
- Immutable logs — sealed event files per discussion
- SQLite index — queryable metrics and relationships
- Curated memory — human-approved patterns and lessons
- Optional vector — for when the corpus grows large
Who it's for
Developers who want more rigor from AI-assisted development — not less AI, but smarter AI collaboration.
People learning to code who want AI that teaches as it builds — every decision is explained, every trade-off is documented.
Try it
Here are three links to get you started:
- Framework Presentation — interactive overview
- How-To Guide — getting started
- GitHub Repo — clone the template
Diviner-Dojo
/
agent_framework_template
AI-Native Agentic Development Framework — a Claude Code template with 11 specialist agents, structured multi-agent review, and automated quality gates
Apache 2.0 licensed. Feedback and contributions welcome.
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