{"product_id":"advanced-ai-rubric-bucket-upgrade-skill-for-codex","title":"Advanced AI Rubric \u0026 Bucket Upgrade Skill for Codex","description":"\u003ch3\u003eAdvanced AI Rubric \u0026amp; Bucket Upgrade Skill for Codex\u003c\/h3\u003e\n\n\u003cp\u003eThe Advanced AI Rubric \u0026amp; Bucket Upgrade Skill for Codex provides developers with the capability to propose and execute rubric or bucket upgrades within Codex. This skill operates in two modes: a comprehensive rubric bump and a lightweight bucket-only recalibration.\u003c\/p\u003e\n\n\u003ch3\u003eWhat this skill does\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eAllows users to propose changes to the scoring rubric using the \u003ccode\u003e--propose\u003c\/code\u003e command, which initiates a robust multi-step review process.\u003c\/li\u003e\n  \u003cli\u003eEnables the adjustment of bucket boundaries without altering the rubric formula via the \u003ccode\u003e--bucket-only\u003c\/code\u003e command, automatically deriving new boundaries.\u003c\/li\u003e\n  \u003cli\u003eEnsures rubric and bucket updates are completed through cheat-score-blind recalibration, using a standard calibration pool for scoring.\u003c\/li\u003e\n  \u003cli\u003eSupports recalibration with a cheat-bump process that includes phase-specific checks and validations, based on user inputs.\u003c\/li\u003e\n  \u003cli\u003eIntegrates independent cross-model review for comprehensive rubric bumps to maintain scoring accuracy.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eWho it is for\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eDevelopers and data scientists leveraging AI coding agents such as Codex, Claude Code, and Cursor.\u003c\/li\u003e\n  \u003cli\u003eTeams managing complex AI models requiring dynamic adjustments to evaluation metrics.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eUse cases\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eRefining AI evaluation metrics where the existing scoring rubric needs significant adjustments for improved model assessments.\u003c\/li\u003e\n  \u003cli\u003eAdjusting evaluation buckets to better fit evolving datasets as project requirements change over time.\u003c\/li\u003e\n  \u003cli\u003eImplementing detailed metric adjustments to cater to new dimensions or weight shifts in AI model evaluations.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch3\u003eTechnical details\u003c\/h3\u003e\n\u003cul\u003e\n  \u003cli\u003eUtilizes \u003ccode\u003echeat-bump\u003c\/code\u003e integration for initiating rubric and bucket modifications.\u003c\/li\u003e\n  \u003cli\u003eImplements a phased approach to execution, beginning with parameter detection and proceeding through recalibration and verification stages.\u003c\/li\u003e\n  \u003cli\u003eEnsures independency in audits, applying comprehensive cross-model reviews for proposed changes to guarantee accuracy.\u003c\/li\u003e\n  \u003cli\u003eRelies on agentic-ai and aiapplication frameworks to facilitate seamless integration with AI development environments like Codex.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c!-- mcpcart:static-blocks:start --\u003e\n\u003chr\u003e\n\u003ch3\u003eSource \u0026amp; Licence\u003c\/h3\u003e\n\u003cp\u003eThis package is built on open-source work published by \u003cstrong\u003eLiHongwei-cn\u003c\/strong\u003e (\u003ca href=\"https:\/\/github.com\/LiHongwei-cn\/lihongwei-cn\" rel=\"nofollow noopener\" target=\"_blank\"\u003eLiHongwei-cn\/lihongwei-cn\u003c\/a\u003e) and distributed under \u003cstrong\u003eMIT\u003c\/strong\u003e. The original licence text and copyright notice are included in your download.\u003c\/p\u003e\n\u003cp\u003ePersonal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.\u003c\/p\u003e\n\u003cp\u003eYour purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.\u003c\/p\u003e\n\u003ch3\u003eDelivery \u0026amp; Support\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eDelivery:\u003c\/strong\u003e instant — a secure download link is emailed to you as soon as payment is confirmed.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eFormat:\u003c\/strong\u003e ZIP archive containing the skill files, documentation and the original licence.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSupport:\u003c\/strong\u003e \u003ca href=\"mailto:support@mcpcart.com\"\u003esupport@mcpcart.com\u003c\/a\u003e — we aim to reply within 2 business days.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eUpdates:\u003c\/strong\u003e updates are included only where stated on this page.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eRefunds\u003c\/h3\u003e\n\u003cp\u003eThis is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.\u003c\/p\u003e\n\u003cp style=\"font-size:0.85em;color:#666;\"\u003eClaude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.\u003c\/p\u003e\n\u003c!-- mcpcart:static-blocks:end --\u003e","brand":"MCP Cart","offers":[{"title":"Default Title","offer_id":53118669259063,"sku":"MCP-LIHONGWEI-CN-LIHONGWEI-CN-CHEAT-BUMP","price":2.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0981\/3950\/4951\/files\/lD5HzPVhm5i7XHYQIpw0L_0df746b04c714bcf9db3467cf8a70fe8.jpg?v=1791457432","url":"https:\/\/mcpcart.com\/products\/advanced-ai-rubric-bucket-upgrade-skill-for-codex","provider":"SPF PRO","version":"1.0","type":"link"}