Portable engineering system for Claude Code with hooks, specialized agents, and self-improvement

A developer frustrated with repeating instructions to Claude Code built a portable engineering system that lives in ~/.claude/ and applies to every project automatically. The system addresses two core problems: the repetition loop where Claude Code would hit the same bug days later and solve it from scratch, and the cross-project disconnect where rules refined in one project didn't exist in another.
System components
The system includes several key components:
- A constitution (CLAUDE.md) – 650 lines of rules with a value hierarchy, decision boundaries, and three execution modes depending on task complexity
- Hooks that enforce rules deterministically – Not suggestions the AI might ignore, but bash scripts that physically block dangerous commands like force pushes, wrong package manager usage, or rm -rf
- Three specialized agents – An orchestrator that delegates but never codes, builders that work in isolated copies of the repo, and a read-only reviewer that can't fix things (only reports)
- A skill pipeline – From planning to building to shipping to production, mostly autonomous with one non-negotiable gate: production deploy always asks
- An immune system – Every error gets logged with the root cause AND approaches that failed. Same bug across 2+ projects becomes a permanent rule, developing antibodies
- Anti-Goodhart verification – Five questions every agent must answer before claiming "done," because "all tests pass" doesn't mean the app works
Compound engineering approach
The system is built on Compound Engineering: Plan → Work → Review → Compound. That fourth step is where the system improves itself. The developer mentions specific rules they previously had to repeat daily: "use pnpm not npm," "don't delete passing tests," and "run tests before committing."
The project is open source at https://github.com/vinicius91carvalho/.claude with a full walkthrough of all 15 pieces available at https://tail-f-thoughts.hashnode.dev/self-improving-engineering-system-claude-code.
📖 Read the full source: r/ClaudeAI
👀 See Also

Gemma4 26B-A4B Delivers Fast Local Performance with Web Search and Image Support
The gemma-4-26B-A4B model achieves approximately 145 tokens per second on an RTX 4090 and includes web search MCP and image support for chat applications. A blog post details setup and cross-platform usage on Mac and iPhone.

hipEngine: Fast Native Qwen 3.6 Inference for RDNA3 (Strix Halo, 7900 XTX)
hipEngine is a new open-source (AGPLv3) ROCm-native inference engine for Qwen 3.6 MoE on RDNA3 GPUs. Benchmarks show prefill up to 2718 tok/s on 7900 XTX, competitive with llama.cpp, and INT8 KV cache enabling full 256K context in under 24GB.

Hollow AgentOS Reduces Claude Code Token Usage by 68.5% with JSON-Native OS Approach
Hollow AgentOS, a JSON-native operating system layer for AI agents, reduces Claude Code token usage by 68.5% by eliminating wasteful shell command overhead. The tool plugs into Claude Code via MCP and runs local inference through Ollama.

HolyCode: Docker Container for Persistent Claude AI Coding Environments
HolyCode is a Docker container that maintains AI coding environment state across machine switches and rebuilds. It includes 30+ preinstalled tools, browser automation with Chromium + xvfb + Playwright, and preserves context in ./data/opencode.