Open Code Review is an open-source CLI tool that uses LLMs to review code diffs and full files with higher precision than general-purpose AI agents while using 9x fewer tokens. It combines deterministic engineering (file selection, rule matching, positioning) with an agent for dynamic decisions, and has been validated across 200 real pull requests from 50 open-source projects.

• Achieves significantly higher precision and F1 scores than Claude Code with the same underlying model, consuming only ~1/9 of the tokens and completing reviews faster
• Uses hard constraints (precise file selection, smart bundling, fine-grained rule matching, external positioning modules) to eliminate common AI agent failures like incomplete coverage and position drift
• Built on production data from Alibaba's internal use across two years serving tens of thousands of developers and identifying millions of defects

This tweet notes that while CLAUDE.md solves the instruction-handling side, you still need to track your model’s context budget. It links to Headroom, a simple one-line-install status bar that shows your current context usage percentage in your editor’s status line.

• Structuring prompts in a defined markdown file (CLAUDE.md) with sections for goals, context, constraints, and examples reduces ambiguity and improves model reliability
• Headroom is a one-line-install status bar tool that displays real-time context window usage percentage directly in the editor's statusline
• Combining CLAUDE.md and headroom addresses two separate problems: instruction clarity and token budget tracking, preventing unexpected conversation truncation