Analyze code and architecture with a deep reasoning model via Codex CLI.
npx skills add https://github.com/trancong12102/ccc --skill oracle-trancong12102
Please help me install this Agent Skill. Skill: oracle Source: https://github.com/trancong12102/ccc/tree/main/core/skills/oracle Command: npx skills add https://github.com/trancong12102/ccc --skill oracle-trancong12102
Invokes OpenAI's GPT-5.2 extra high reasoning model via CLI for complex analysis tasks. It excels at debugging, code review, architecture analysis, and finding better solutions.
Provide a deep reasoning analysis for the given codebase or architecture prompt using the codex CLI with the oracle profile.
High-intent search queries and answers about installing and using this skill.
Analyze complex code architecture by running a deep reasoning model that surfaces design issues and provides strategic recommendations. This approach applies to code reviews and architectural refactors, delivering actionable guidance and suggested fixes for multi-file collaboration.
Get a second opinion on a critical bug by invoking a deep reasoning model to analyze the issue. This provides concrete next steps and strategic debugging guidance, helping you uncover hidden issues and obtain actionable fixes for high-impact decisions.
Yes, Codex CLI authentication is required to use this deep reasoning model for code review. You must also provide file references using the @ syntax so the model can analyze your specific codebase and output actionable guidance.
Yes, you can use deep reasoning to find better solutions for system design challenges. It analyzes complex design decisions to uncover underlying issues and provides strategic recommendations, offering concrete next steps for architectural improvements.
Use an oracle profile for architectural refactors when facing high-impact decisions or analyzing complex codebases. It excels at deep analysis of design choices, surfacing issues, and providing strategic recommendations with actionable guidance and suggested fixes.
Yes, deep reasoning analysis works with multi-file collaboration by using file references provided via @ syntax. It processes these references to deliver deep insight into system design challenges and architectural decisions, outputting actionable guidance.
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