OpenAI Official Plugin Strongly Integrated into Claude Code

marsbit2026-03-31 tarihinde yayınlandı2026-03-31 tarihinde güncellendi

Özet

OpenAI has officially released the "codex-plugin-cc" on GitHub, enabling developers to integrate OpenAI’s Codex model capabilities directly into Anthropic’s command-line development tool, Claude Code. This cross-platform integration breaks down ecosystem barriers between major AI tools, allowing developers to leverage the strengths of both models without switching environments. With simple configuration, Claude Code becomes a versatile programming assistant combining the advantages of both companies. Key features include: - Standard code review via the `/codex:review` command, providing expert improvement recommendations and double-checking for logic errors. - Adversarial review using `/codex:adversarial-review`, which challenges design decisions to identify potential performance bottlenecks or security risks. - Task delegation through `/codex:rescue`, allowing complex debugging or repair tasks to be handed off to a Codex sub-agent for collaborative problem-solving. This integration enhances code quality and development efficiency through multi-model collaboration.

Recently, the AI developer community welcomed a major update: OpenAI officially released an open-source project named codex-plugin-cc on GitHub. This plugin allows developers to directly utilize the capabilities of OpenAI's Codex model within the command-line development tool Claude Code, introduced by Anthropic.

This "cross-brand" integration breaks down the ecosystem barriers that previously existed between major AI model tools, enabling developers to leverage the technical strengths of both industry giants without switching environments. With simple command configurations, Claude Code instantly transforms into an all-in-one programming assistant that combines the best of both.

Empowered by this plugin, users can initiate a standard read-only code review using the /codex:review command to receive professional improvement suggestions from Codex. This dual verification mechanism effectively catches logical vulnerabilities that a single model might miss, adding a "double insurance" for code quality.

More uniquely, its "adversarial review" feature allows developers to use /codex:adversarial-review to actively request Codex to challenge existing design decisions. This mode is specifically designed to stress-test the rationality of system architecture, uncovering potential performance bottlenecks or security risks from a "fault-finding" perspective.

Additionally, the plugin introduces a task delegation mechanism, enabling users to transfer complex debugging or repair tasks to a Codex sub-agent via /codex:rescue. This collaborative model achieves automatic task distribution, allowing the primary model and auxiliary models to each focus on their respective areas of expertise.

github:https://github.com/openai/codex-plugin-cc

İlgili Sorular

QWhat is the name of the official OpenAI plugin that integrates with Claude Code?

AThe plugin is called codex-plugin-cc.

QWhat is the primary function of the /codex:review command in the new plugin?

AThe /codex:review command is used to initiate a standard read-only code review to get professional improvement suggestions from the Codex model.

QWhat unique feature does the /codex:adversarial-review command provide?

AThe /codex:adversarial-review command enables an 'adversarial review' function, which actively challenges existing design decisions to stress-test the system architecture and uncover potential performance bottlenecks or security risks.

QHow does the /codex:rescue command facilitate task management?

AThe /codex:rescue command allows users to delegate complex debugging or repair tasks to a Codex sub-agent, enabling a collaborative model where the main and auxiliary models work in their respective areas of expertise.

QWhere was the codex-plugin-cc project officially released?

AThe project was officially released by OpenAI on GitHub.

İlgili Okumalar

Eight Years of Entrepreneurship Notes from a16z's AI Partner

An early generative AI entrepreneur reflects on his 8-year journey building Rosebud AI, founded in 2018—a time when the field was still called “synthetic media.” Initially experimenting with models like CycleGAN and StyleGAN, he believed AI could make creation as intuitive as playing a game. Over the years, his team launched multiple products, including the viral app TokkingHeads, which gained 2 million users, learning to design around imperfect model outputs to deliver “good enough” user experiences. The evolution from niche synthetic media to general-purpose AI infrastructure—especially after GPT-4’s release—reshaped product possibilities. Code generation matured enough by 2023 to enable text-to-game prototyping. The author emphasizes that the real differentiator now isn’t just model capability but product design, distribution, and business model innovation. Having stepped down as CEO of Rosebud AI, he joins a16z as a partner focused on investing in the frontier model stack—models, infrastructure, and tools. He remains optimistic about AI-driven progress in creative tools, coding, and scientific domains. The piece concludes with a forward-looking note: the next phase of AI will be less about what’s possible and more about how capabilities are productized and scaled in the real world.

marsbit17 dk önce

Eight Years of Entrepreneurship Notes from a16z's AI Partner

marsbit17 dk önce

How Many Tokens Away Is Yang Zhilin from the 'Moon Chasing the Light'?

The article explores the intense competition between two leading Chinese AI companies, DeepSeek and Kimi (Moon Dark Side), and the mounting pressure on Yang Zhilin, the founder of Kimi. While DeepSeek re-emerged after 15 months of silence with its powerful V4 model—boasting 1.6 trillion parameters and low-cost, long-context capabilities—Kimi has been focusing on long-context processing and multi-agent systems with its K2.6 model. Yang faces a threefold challenge: technological rivalry, commercialization pressure, and investor expectations. Despite Kimi’s high valuation (reaching $18 billion), its revenue heavily relies on a single product with low paid conversion rates, while DeepSeek’s strategic silence and open-source influence have strengthened its market position and valuation prospects, now targeting over $20 billion. Both companies reflect broader trends in China’s AI ecosystem: Kimi aims for global influence through open-source contributions and agent-based advancements, while DeepSeek prioritizes foundational innovation and hardware independence, notably shifting to Huawei’s chips. Their competition is seen as vital for China’s AI progress, with the gap between top Chinese and U.S. models narrowing to just 2.7% on the Elo rating scale. Ultimately, the article argues that this rivalry, though anxiety-inducing for leaders like Zhilin, is essential for driving innovation and solidifying China’s role in the global AI landscape.

marsbit55 dk önce

How Many Tokens Away Is Yang Zhilin from the 'Moon Chasing the Light'?

marsbit55 dk önce

TechFlow Intelligence Bureau: ChatGPT Helps Amateur Mathematician Crack 60-Year-Old Problem, CFTC Sues New York Regulator Over Coinbase and Gemini

An amateur mathematician, with the assistance of ChatGPT, has solved a combinatorial mathematics puzzle originally proposed by Hungarian mathematician Paul Erdős in the 1960s. This marks another milestone in AI-aided mathematical research, demonstrating the evolving capabilities of large language models in formal reasoning. In other AI developments, OpenAI introduced a new privacy filter tool for enterprise API usage, automatically screening sensitive data. Meanwhile, the Qwen3.6-27B model achieved 100 tokens per second on a single RTX 5090 GPU using quantization, significantly lowering the cost barrier for local AI deployment. In crypto and Web3, the U.S. CFTC sued New York’s financial regulator, challenging its oversight of Coinbase and Gemini—a first-of-its-kind federal-state regulatory clash. Following a vulnerability, KelpDAO and major DeFi protocols established a recovery fund. Tether froze $344 million in assets linked to Iran’s central bank upon U.S. Treasury request, highlighting the centralized control risks in stablecoins. Separately, Litecoin underwent a 3-hour chain reorganization to undo a privacy-layer exploit. In the U.S., former President Trump invoked the Defense Production Act to address power grid bottlenecks affecting AI data centers and dismissed the entire National Science Board, raising concerns over research independence. A retail trader gained 250% on a $600k Intel options bet amid AI-related speculation. Xiaomi announced its first performance electric vehicle, targeting rivals like Tesla. Meanwhile, iPhone users reported devices automatically reinstalling a hidden app daily, suspected to be MDM-related. A Chinese securities report noted that A-share institutional crowding has reached its second-longest streak since 2007, signaling high valuations and potential style rotation. The day’s developments reflect a dual narrative: AI is enabling unprecedented individual breakthroughs, while centralized power structures—whether governmental or corporate—are becoming more assertive, underscoring that decentralization is as much a political-economic challenge as a technical one.

marsbit1 saat önce

TechFlow Intelligence Bureau: ChatGPT Helps Amateur Mathematician Crack 60-Year-Old Problem, CFTC Sues New York Regulator Over Coinbase and Gemini

marsbit1 saat önce

Iran’s Crypto Lifeline Hit As US Freezes $344 Million In Funds

The US Treasury has frozen $344 million in cryptocurrency tied to Iranian military and political groups, specifically targeting two Tron blockchain wallets connected to the Islamic Revolutionary Guard Corps and Hizballah. This action follows reports that Iran was collecting Bitcoin payments from ships for safe passage through the Strait of Hormuz. The freeze occurred just one day after stablecoin issuer Tether locked the same amount of funds at the request of US law enforcement. The move is part of broader US efforts to disrupt Iran's ability to generate and move funds, highlighting the limitations of using cryptocurrency as a sanctions workaround when centralized issuers comply with enforcement actions.

bitcoinist2 saat önce

Iran’s Crypto Lifeline Hit As US Freezes $344 Million In Funds

bitcoinist2 saat önce

Amidst the Volatility in the Crypto Market, Who is Buying Against the Trend?

"In a volatile crypto market downturn of Q1 2026, institutional players demonstrated divergent strategies. While Bitcoin fell over 25% and Ethereum dropped 35%, key institutions accumulated: corporate treasuries like Strategy (MicroStrategy) added over $10 billion in BTC, sovereign wealth funds like Mubadala increased IBIT holdings by 46%, and major banks launched crypto services and ETFs. Notably, 26 new crypto ETFs were filed or launched under streamlined SEC rules, including bank-led products from Morgan Stanley and BlackRock’s staking ETH ETF. VC funding saw concentration: total investment reached ~$5 billion, but deal count plummeted 49%. Three mega-deals—BVNK ($1.8B), Kalshi ($1B), and Polymarket ($600M)—accounted for half the quarter’s funding. Investment shifted from DeFi/NFTs to payments, prediction markets, and regulated CeFi infrastructure. Selling pressure came from hedge funds (e.g., Brevan Howard cut IBIT by 85%) and Bitcoin miners liquidating holdings. The U.S. strategic Bitcoin reserve saw zero additions, highlighting that real buying came from corporations and sovereign funds, not governments. The institutional crypto landscape is bifurcating: long-term holders accumulate while short-term traders exit, signaling a foundation for the next cycle."

marsbit2 saat önce

Amidst the Volatility in the Crypto Market, Who is Buying Against the Trend?

marsbit2 saat önce

İşlemler

Spot

Futures