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open-code-review/ROADMAP.md
kite 8a987d3d29 docs: add ROADMAP.md with project direction for the next year 
Cover planned work (JetBrains plugin, standard MCP integration,
Ultra mode, domain-specific long-term memory) and explicit non-goals.
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Roadmap

This document describes the planned direction for OpenCodeReview over the next year. It is a living document and will be updated as priorities evolve.

Feedback is welcome via GitHub Discussions or Issues.

Current State (Mid-2026)

OpenCodeReview currently provides:

  • A CLI tool (ocr) for AI-powered code review with deterministic engineering and agent hybrid architecture.
  • Integration with coding agents: Claude Code (plugin/skill), Codex (plugin), and Cursor (plugin).
  • A VSCode extension for in-editor code review.
  • CI/CD integration (GitHub Actions, GitLab CI, etc.).
  • Multi-provider LLM support (OpenAI-compatible, Anthropic, Google Gemini, Amazon Bedrock, Azure OpenAI, etc.).
  • Review rules engine with per-file pattern matching.
  • Multi-language documentation (English, Chinese, Japanese, Korean, Russian).

Planned — H2 2026

IDE Plugins

  • JetBrains plugin — Bring AI code review to IntelliJ IDEA, GoLand, PyCharm, and other JetBrains IDEs with the same capabilities as the existing VSCode extension.

MCP Integration

  • Standard MCP server — Expose OpenCodeReview as a Model Context Protocol server, allowing users to integrate external context tools (documentation retrieval, issue trackers, internal knowledge bases) into the review process through the standard MCP interface.

Ultra Mode

  • Higher-recall review mode — An opt-in mode that trades increased token consumption and review time for significantly higher issue recall rate. Designed for security-sensitive or high-risk changesets where thoroughness is more important than speed.

Planned — H1 2027

Domain-Specific Long-Term Memory

  • Persistent review knowledge — Enable the review engine to accumulate domain-specific knowledge over time (recurring patterns, past review decisions, project-specific conventions) and apply it to future reviews, improving relevance and reducing repeated feedback.

Not Planned

The following are explicitly out of scope for the foreseeable future:

  • Automated code fixing without human review — OCR is a review tool, not an auto-fix tool. While it can suggest fixes, applying changes always requires human approval.
  • General-purpose AI coding assistant — OCR focuses exclusively on code review. Features like code generation, refactoring, or chat-based coding assistance are not planned.
  • Self-hosted LLM bundling — OCR connects to external LLM providers but does not bundle or host models itself.