Score breakdown
Popularity is tracked separately. Support, ads, sponsorships, and tips never affect these signals.
Why it matters
Useful for any Claude Code user who wants to delegate reviews + tasks to Codex without leaving the Claude Code workflow. The durable differentiator is that this plugin is officially from OpenAI and binds Codex into Claude Code as a side-by-side agent instead of a parallel CLI — `/codex:review` runs on the current uncommitted changes or a `--base <ref>` branch, returns whatever reviews Codex itself
Who should use it
Who should skip it
Skip openai/codex-plugin-cc if the source repository or demo is inactive, unmaintained, or no longer matches the description shown here.
About this signal
openai/codex-plugin-cc is tracked by RepoRadar as a official openai claude code plug in the Agent Infrastructure section. It was first seen on 2026-07-04 and last updated on 2026-07-04. The current verdict is 'try now' with a Gold tier and review needed setup difficulty. openai/codex-plugin-cc leads on workflow potential (10.0) and practical usefulness (9.0); its lowest signal is momentum (3.5), so factor that in before investing setup time. This page summarizes the evidence RepoRadar has captured from captured source metadata. The score, tier, risk label, and verdict on this page are never influenced by sponsorship, ads, or tips — they reflect only the usefulness, popularity, novelty, momentum, maturity, and evidence signals described in the RepoRadar methodology.
How this item is evaluated
RepoRadar assigned openai/codex-plugin-cc a composite score of 8.6 out of 10, placing it in the Gold tier. This score combines weighted sub-signals: usefulness (35%), novelty (18%), momentum (14%), maturity (10%), open-source/build quality (7%), evidence quality (6%), workflow potential (6%), and setup ease (4%). Popularity is tracked separately at 9.0 and never affects the composite score or tier. The risk label of 'low' reflects inherent user-impacting hazards, not generic novelty. Items with no risk flag may still require normal code review before production use.
Putting this into practice? Read How to vet an AI agent or MCP server before you wire it in for the checklist behind this score.
Risk explanation
Risk label is still being reviewed from the captured evidence. Treat the item as unknown-risk until you review the linked source, permissions, setup path, and data access.