Execute external LLM code reviews using Codex CLI and Gemini CLI.
npx skills add https://github.com/blacktop/dotfiles --skill second-opinion-blacktop
Please help me install this Agent Skill. Skill: second-opinion Source: https://github.com/blacktop/dotfiles/tree/main/ai/skills/second-opinion Command: npx skills add https://github.com/blacktop/dotfiles --skill second-opinion-blacktop
This Skill provides an external, AI-driven code review to identify potential issues and offer alternative perspectives on code changes, enhancing code quality and reducing risks.
Use the second-opinion skill to get a review of your uncommitted changes using both Codex and Gemini.
High-intent search queries and answers about installing and using this skill.
To perform an AI code review on uncommitted changes, use this Skill to execute external LLM analysis via Codex CLI and Gemini CLI. It evaluates code changes to identify potential issues in correctness, security, performance, and maintainability.
Yes, you can review branch diffs and specific commits with external LLMs. This Skill supports analyzing various scopes including uncommitted changes, branch diffs, individual commits, and GitHub pull requests using Codex CLI and Gemini CLI.
Using multiple LLMs for code analysis provides an independent, external perspective on code changes. By leveraging both Codex and Gemini, you get a comprehensive review that catches overlooked vulnerabilities and inefficiencies, enhancing overall code quality and reducing risks.
Yes, this AI code review tool works with GitHub pull requests. It executes external LLM code reviews using Codex CLI and Gemini CLI to analyze pull requests and identify potential issues across correctness, security, performance, and maintainability.
You need to have Codex CLI and Gemini CLI available in your environment to use this Skill. These external tools are leveraged to execute the AI-driven code reviews across various scopes like uncommitted changes, branch diffs, commits, and pull requests.
You should use an external LLM code review when you need an independent perspective on potential issues related to correctness, security, performance, and maintainability. It is ideal before merging critical feature branches to catch overlooked vulnerabilities that standard linters might miss.
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