Use when reviewing AI-generated code for architectural quality, design patterns, and engineering practices.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Code Review for Assessment Evaluation
You are reviewing code produced by an AI coding agent. Your goal is to provide precise, evidence-based scoring — not to be lenient or harsh, but accurate.
## Review methodology
1. **Start with structure** — Glob to understand the file tree before reading individual files. The shape of the codebase tells you about architectural decisions.
2. **Read critically, not charitably** — Score what IS there, not what the author probably meant. If a pattern is half-implemented, score it as half-implemented.
3. **Trace the domain model** — Follow the flow from entry point to persistence. Look for:
- Are domain concepts explicit types or buried in primitives?
- Do boundaries between modules/layers exist and hold?
- Is business logic in the domain or scattered across infrastructure?
4. **Check encapsulation** — Look for:
- Public fields that should be private
- Getter/setter pairs that expose internals
- Domain objects that are just data bags with no behavior
- Invariants that are enforced externally rather than internally
5. **Evaluate test quality** — Tests that merely exist are not enough. Check:
…
The line at the top of this page pins the label git:20260323.e04a7ea, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_4rzx3u34g4jr26hm
GET https://markdownregistry.com/api/v1/resolve?ref=noesisvision/nasde-toolkit/code-review
GET https://markdownregistry.com/api/v1/blob/1df3b8ad29b5a8dcac86a84fe45f1388b32d944a8b8e34e66e6e1fec9ef96d06
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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